Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling

PubMed Central

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

Background: The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. Objective: The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. Materials and Methods: The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. Results: The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. Conclusion: The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates. PMID:24748752

Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling.

PubMed

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates.

Analysis of simple 2-D and 3-D metal structures subjected to fragment impact

NASA Technical Reports Server (NTRS)

Witmer, E. A.; Stagliano, T. R.; Spilker, R. L.; Rodal, J. J. A.

1977-01-01

Theoretical methods were developed for predicting the large-deflection elastic-plastic transient structural responses of metal containment or deflector (C/D) structures to cope with rotor burst fragment impact attack. For two-dimensional C/D structures both, finite element and finite difference analysis methods were employed to analyze structural response produced by either prescribed transient loads or fragment impact. For the latter category, two time-wise step-by-step analysis procedures were devised to predict the structural responses resulting from a succession of fragment impacts: the collision force method (CFM) which utilizes an approximate prediction of the force applied to the attacked structure during fragment impact, and the collision imparted velocity method (CIVM) in which the impact-induced velocity increment acquired by a region of the impacted structure near the impact point is computed. The merits and limitations of these approaches are discussed. For the analysis of 3-d responses of C/D structures, only the CIVM approach was investigated.

AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures

PubMed Central

Zambrano, Rafael; Jamroz, Michal; Szczasiuk, Agata; Pujols, Jordi; Kmiecik, Sebastian; Ventura, Salvador

2015-01-01

Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties to predict the aggregation properties of folded globular proteins, where aggregation-prone sites are often not contiguous in sequence or buried inside the native structure. The AGGRESCAN3D (A3D) server overcomes these limitations by taking into account the protein structure and the experimental aggregation propensity scale from the well-established AGGRESCAN method. Using the A3D server, the identified aggregation-prone residues can be virtually mutated to design variants with increased solubility, or to test the impact of pathogenic mutations. Additionally, A3D server enables to take into account the dynamic fluctuations of protein structure in solution, which may influence aggregation propensity. This is possible in A3D Dynamic Mode that exploits the CABS-flex approach for the fast simulations of flexibility of globular proteins. The A3D server can be accessed at http://biocomp.chem.uw.edu.pl/A3D/. PMID:25883144

LECTINPred: web Server that Uses Complex Networks of Protein Structure for Prediction of Lectins with Potential Use as Cancer Biomarkers or in Parasite Vaccine Design.

PubMed

Munteanu, Cristian R; Pedreira, Nieves; Dorado, Julián; Pazos, Alejandro; Pérez-Montoto, Lázaro G; Ubeira, Florencio M; González-Díaz, Humberto

2014-04-01

Lectins (Ls) play an important role in many diseases such as different types of cancer, parasitic infections and other diseases. Interestingly, the Protein Data Bank (PDB) contains +3000 protein 3D structures with unknown function. Thus, we can in principle, discover new Ls mining non-annotated structures from PDB or other sources. However, there are no general models to predict new biologically relevant Ls based on 3D chemical structures. We used the MARCH-INSIDE software to calculate the Markov-Shannon 3D electrostatic entropy parameters for the complex networks of protein structure of 2200 different protein 3D structures, including 1200 Ls. We have performed a Linear Discriminant Analysis (LDA) using these parameters as inputs in order to seek a new Quantitative Structure-Activity Relationship (QSAR) model, which is able to discriminate 3D structure of Ls from other proteins. We implemented this predictor in the web server named LECTINPred, freely available at http://bio-aims.udc.es/LECTINPred.php. This web server showed the following goodness-of-fit statistics: Sensitivity=96.7 % (for Ls), Specificity=87.6 % (non-active proteins), and Accuracy=92.5 % (for all proteins), considering altogether both the training and external prediction series. In mode 2, users can carry out an automatic retrieval of protein structures from PDB. We illustrated the use of this server, in operation mode 1, performing a data mining of PDB. We predicted Ls scores for +2000 proteins with unknown function and selected the top-scored ones as possible lectins. In operation mode 2, LECTINPred can also upload 3D structural models generated with structure-prediction tools like LOMETS or PHYRE2. The new Ls are expected to be of relevance as cancer biomarkers or useful in parasite vaccine design. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemical Structural Novelty: On-Targets and Off-Targets

PubMed Central

Yera, Emmanuel R.; Cleves, Ann. E.; Jain, Ajay N.

2011-01-01

Drug structures may be quantitatively compared based on 2D topological structural considerations and based on 3D characteristics directly related to binding. A framework for combining multiple similarity computations is presented along with its systematic application to 358 drugs with overlapping pharmacology. Given a new molecule along with a set of molecules sharing some biological effect, a single score based on comparison to the known set is produced, reflecting either 2D similarity, 3D similarity, or their combination. For prediction of primary targets, the benefit of 3D over 2D was relatively small, but for prediction of off-targets, the added benefit was large. In addition to assessing prediction, the relationship between chemical similarity and pharmacological novelty was studied. Drug pairs that shared high 3D similarity but low 2D similarity (i.e. a novel scaffold) were shown to be much more likely to exhibit pharmacologically relevant differences in terms of specific protein target modulation. PMID:21916467

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

Molecular Phylogeny and Predicted 3D Structure of Plant beta-D-N-Acetylhexosaminidase

PubMed Central

Hossain, Md. Anowar

2014-01-01

beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom. PMID:25165734

Local backbone structure prediction of proteins

PubMed Central

De Brevern, Alexandre G.; Benros, Cristina; Gautier, Romain; Valadié, Hélène; Hazout, Serge; Etchebest, Catherine

2004-01-01

Summary A statistical analysis of the PDB structures has led us to define a new set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one is defined by the (φ, Ψ) dihedral angles of 5 consecutive residues. The amino acid distributions observed in sequence windows encompassing these PBs are used to predict by a Bayesian approach the local 3D structure of proteins from the sole knowledge of their sequences. LocPred is a software which allows the users to submit a protein sequence and performs a prediction in terms of PBs. The prediction results are given both textually and graphically. PMID:15724288

AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures.

PubMed

Zambrano, Rafael; Jamroz, Michal; Szczasiuk, Agata; Pujols, Jordi; Kmiecik, Sebastian; Ventura, Salvador

2015-07-01

Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties to predict the aggregation properties of folded globular proteins, where aggregation-prone sites are often not contiguous in sequence or buried inside the native structure. The AGGRESCAN3D (A3D) server overcomes these limitations by taking into account the protein structure and the experimental aggregation propensity scale from the well-established AGGRESCAN method. Using the A3D server, the identified aggregation-prone residues can be virtually mutated to design variants with increased solubility, or to test the impact of pathogenic mutations. Additionally, A3D server enables to take into account the dynamic fluctuations of protein structure in solution, which may influence aggregation propensity. This is possible in A3D Dynamic Mode that exploits the CABS-flex approach for the fast simulations of flexibility of globular proteins. The A3D server can be accessed at http://biocomp.chem.uw.edu.pl/A3D/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins

PubMed Central

Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong; Weiner, Brian E.; Fischer, Axel W.; Meiler, Jens

2017-01-01

Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein–membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein–membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein–protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org. PMID:26804342

High Cycle Fatigue Prediction for Mistuned Bladed Disks with Fully Coupled Fluid-Structural Interaction

DTIC Science & Technology

2006-06-01

response (time domain) structural vibration model for mistuned rotor bladed disk based on the efficient SNM model has been developed. The vi- bration...airfoil and 3D wing, unsteady vortex shedding of a stationary cylinder, induced vibration of a cylinder, forced vibration of a pitching airfoil, induced... vibration and flutter boundary of 2D NACA 64A010 transonic airfoil, 3D plate wing structural response. The predicted results agree well with benchmark

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

PubMed

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on docking calculations with biochemical pathways and enables users to easily and quickly assess PPI feasibilities by archiving PPI predictions. MEGADOCK-Web also promotes the discovery of new PPIs and protein functions and is freely available for use at http://www.bi.cs.titech.ac.jp/megadock-web/ .

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

Changes in quantitative 3D shape features of the optic nerve head associated with age

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2013-02-01

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

PubMed

Theis, Corinna; Höner Zu Siederdissen, Christian; Hofacker, Ivo L; Gorodkin, Jan

2013-12-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.

Mining the protein data bank with CReF to predict approximate 3-D structures of polypeptides.

PubMed

Dorn, Márcio; de Souza, Osmar Norberto

2010-01-01

n this paper we describe CReF, a Central Residue Fragment-based method to predict approximate 3-D structures of polypeptides by mining the Protein Data Bank (PDB). The approximate predicted structures are good enough to be used as starting conformations in refinement procedures employing state-of-the-art molecular mechanics methods such as molecular dynamics simulations. CReF is very fast and we illustrate its efficacy in three case studies of polypeptides whose sizes vary from 34 to 70 amino acids. As indicated by the RMSD values, our initial results show that the predicted structures adopt the expected fold, similar to the experimental ones.

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.

PubMed

Deng, Lei; Fan, Chao; Zeng, Zhiwen

2017-12-28

Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding and protein 3D structure. Thus, accurately predicting these features is a critical step for 3D protein structure building. In this study, we present DeepSacon, a computational method that can effectively predict protein solvent accessibility and contact number by using a deep neural network, which is built based on stacked autoencoder and a dropout method. The results demonstrate that our proposed DeepSacon achieves a significant improvement in the prediction quality compared with the state-of-the-art methods. We obtain 0.70 three-state accuracy for solvent accessibility, 0.33 15-state accuracy and 0.74 Pearson Correlation Coefficient (PCC) for the contact number on the 5729 monomeric soluble globular protein dataset. We also evaluate the performance on the CASP11 benchmark dataset, DeepSacon achieves 0.68 three-state accuracy and 0.69 PCC for solvent accessibility and contact number, respectively. We have shown that DeepSacon can reliably predict solvent accessibility and contact number with stacked sparse autoencoder and a dropout approach.

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

PubMed

Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

2017-11-14

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

STRUCTURAL SCALE LIFE PREDICTION OF AERO STRUCTURES EXPERIENCING COMBINED EXTREME ENVIRONMENTS

DTIC Science & Technology

2017-07-01

representation is converted into a tetrahedral FE mesh using the software DREAM .3D. Due to a special voxel-identification scheme the FE mesh includes...research team met with DREAM .3D developers at AFRL (Drs. Mike Groeber and Sean Donegan) to discuss possible solutions. Together, the group proposed the...development of a DREAM .3D extension that can leverage the topological data structure within DREAM .3D instead of relying on an image-based

USM3D Predictions of Supersonic Nozzle Flow

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Elmiligui, Alaa A.; Campbell, Richard L.; Nayani, Sudheer N.

2014-01-01

This study focused on the NASA Tetrahedral Unstructured Software System CFD code (USM3D) capability to predict supersonic plume flow. Previous studies, published in 2004 and 2009, investigated USM3D's results versus historical experimental data. This current study continued that comparison however focusing on the use of the volume souring to capture the shear layers and internal shock structure of the plume. This study was conducted using two benchmark axisymmetric supersonic jet experimental data sets. The study showed that with the use of volume sourcing, USM3D was able to capture and model a jet plume's shear layer and internal shock structure.

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.

3D FSE Cube and VIPR-aTR 3.0 Tesla magnetic resonance imaging predicts canine cranial cruciate ligament structural properties.

PubMed

Racette, Molly; Al saleh, Habib; Waller, Kenneth R; Bleedorn, Jason A; McCabe, Ronald P; Vanderby, Ray; Markel, Mark D; Brounts, Sabrina H; Block, Walter F; Muir, Peter

2016-03-01

Estimation of cranial cruciate ligament (CrCL) structural properties in client-owned dogs with incipient cruciate rupture would be advantageous. The objective of this study was to determine whether magnetic resonance imaging (MRI) measurement of normal CrCL volume in an ex-vivo canine model predicts structural properties. Stifles from eight dogs underwent 3.0 Tesla 3D MRI. CrCL volume and normalized median grayscale values were determined using 3D Fast Spin Echo (FSE) Cube and Vastly under-sampled Isotropic PRojection (VIPR)-alternative repetition time (aTR) sequences. Stifles were then mechanically tested. After joint laxity testing, CrCL structural properties were determined, including displacement at yield, yield load, load to failure, and stiffness. Yield load and load to failure (R(2)=0.56, P <0.01) were correlated with CrCL volume determined by VIPR-aTR. Yield load was also correlated with CrCL volume determined by 3D FSE Cube (R(2)=0.32, P <0.05). Structural properties were not related to median grayscale values. Joint laxity and CrCL stiffness were not related to MRI parameters, but displacement at yield load was related to CrCL volume for both sequences during testing (R(2)>0.57, P <0.005). In conclusion, 3D MRI offers a predictive method for estimating canine CrCL structural properties. 3D MRI may be useful for monitoring CrCL properties in clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Online interactive analysis of protein structure ensembles with Bio3D-web.

PubMed

Skjærven, Lars; Jariwala, Shashank; Yao, Xin-Qiu; Grant, Barry J

2016-11-15

Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics. Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no. © The Author 2016. Published by Oxford University Press.

Structural protein descriptors in 1-dimension and their sequence-based predictions.

PubMed

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

Structural prediction and analysis of VIH-related peptides from selected crustacean species.

PubMed

Nagaraju, Ganji Purna Chandra; Kumari, Nunna Siva; Prasad, Ganji Lakshmi Vara; Rajitha, Balney; Meenu, Madan; Rao, Manam Sreenivasa; Naik, Bannoth Reddya

2009-08-17

The tentative elucidation of the 3D-structure of vitellogenesis inhibiting hormone (VIH) peptides is conversely underprivileged by difficulties in gaining enough peptide or protein, diffracting crystals, and numerous extra technical aspects. As a result, no structural information is available for VIH peptide sequences registered in the Genbank. In this situation, it is not surprising that predictive methods have achieved great interest. Here, in this study the molt-inhibiting hormone (MIH) of the kuruma prawn (Marsupenaeus japonicus) is used, to predict the structure of four VIHrelated peptides in the crustacean species. The high similarity of the 3D-structures and the calculated physiochemical characteristics of these peptides suggest a common fold for the entire family.

3D MI-DRAGON: new model for the reconstruction of US FDA drug- target network and theoretical-experimental studies of inhibitors of rasagiline derivatives for AChE.

PubMed

Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Alonso, Nerea; Caamaño, Olga; Yañez, Matilde; González-Díaz, Humberto

2012-01-01

The number of neurodegenerative diseases has been increasing in recent years. Many of the drug candidates to be used in the treatment of neurodegenerative diseases present specific 3D structural features. An important protein in this sense is the acetylcholinesterase (AChE), which is the target of many Alzheimer's dementia drugs. Consequently, the prediction of Drug-Protein Interactions (DPIs/nDPIs) between new drug candidates and specific 3D structure and targets is of major importance. To this end, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out a rational DPIs prediction. Unfortunately, many previous QSAR models developed to predict DPIs take into consideration only 2D structural information and codify the activity against only one target. To solve this problem we can develop some 3D multi-target QSAR (3D mt-QSAR) models. In this study, using the 3D MI-DRAGON technique, we have introduced a new predictor for DPIs based on two different well-known software. We have used the MARCH-INSIDE (MI) and DRAGON software to calculate 3D structural parameters for drugs and targets respectively. Both classes of 3D parameters were used as input to train Artificial Neuronal Network (ANN) algorithms using as benchmark dataset the complex network (CN) made up of all DPIs between US FDA approved drugs and their targets. The entire dataset was downloaded from the DrugBank database. The best 3D mt-QSAR predictor found was an ANN of Multi-Layer Perceptron-type (MLP) with profile MLP 37:37-24-1:1. This MLP classifies correctly 274 out of 321 DPIs (Sensitivity = 85.35%) and 1041 out of 1190 nDPIs (Specificity = 87.48%), corresponding to training Accuracy = 87.03%. We have validated the model with external predicting series with Sensitivity = 84.16% (542/644 DPIs; Specificity = 87.51% (2039/2330 nDPIs) and Accuracy = 86.78%. The new CNs of DPIs reconstructed from US FDA can be used to explore large DPI databases in order to discover both new drugs and/or targets. We have carried out some theoretical-experimental studies to illustrate the practical use of 3D MI-DRAGON. First, we have reported the prediction and pharmacological assay of 22 different rasagiline derivatives with possible AChE inhibitory activity. In this work, we have reviewed different computational studies on Drug- Protein models. First, we have reviewed 10 studies on DP computational models. Next, we have reviewed 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find Drug-Protein QSAR models. Last, we have developped a 3D multi-target QSAR (3D mt-QSAR) models for the prediction of the activity of new compounds against different targets or the discovery of new targets.

3D flexible alignment using 2D maximum common substructure: dependence of prediction accuracy on target-reference chemical similarity.

PubMed

Kawabata, Takeshi; Nakamura, Haruki

2014-07-28

A protein-bound conformation of a target molecule can be predicted by aligning the target molecule on the reference molecule obtained from the 3D structure of the compound-protein complex. This strategy is called "similarity-based docking". For this purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences with the reference molecule. The correspondences are obtained by the maximum common substructure (MCS) of 2D chemical structures, using our program kcombu. The prediction performance was evaluated using many target-reference pairs of superimposed ligand 3D structures on the same protein in the PDB, with different ranges of chemical similarity. The details of atomic correspondence largely affected the prediction success. We found that topologically constrained disconnected MCS (TD-MCS) with the simple element-based atomic classification provides the best prediction. The crashing potential energy with the receptor protein improved the performance. We also found that the RMSD between the predicted and correct target conformations significantly correlates with the chemical similarities between target-reference molecules. Generally speaking, if the reference and target compounds have more than 70% chemical similarity, then the average RMSD of 3D conformations is <2.0 Å. We compared the performance with a rigid-body molecular alignment program based on volume-overlap scores (ShaEP). Our MCS-based flexible alignment program performed better than the rigid-body alignment program, especially when the target and reference molecules were sufficiently similar.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms.

PubMed

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S

2006-12-21

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H(+)(H(2)O)(7). For H(+)(H(2)O)(7) the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Moller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H(+)(H(2)O)(7) [though nearly isoenergetic to the 3D structure for D(+)(D(2)O)(7)]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms

NASA Astrophysics Data System (ADS)

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S.

2006-12-01

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H+(H2O)7. For H+(H2O)7 the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Møller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H+(H2O)7 [though nearly isoenergetic to the 3D structure for D+(D2O)7]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Deformation behaviors of three-dimensional graphene honeycombs under out-of-plane compression: Atomistic simulations and predictive modeling

NASA Astrophysics Data System (ADS)

Meng, Fanchao; Chen, Cheng; Hu, Dianyin; Song, Jun

2017-12-01

Combining atomistic simulations and continuum modeling, a comprehensive study of the out-of-plane compressive deformation behaviors of equilateral three-dimensional (3D) graphene honeycombs was performed. It was demonstrated that under out-of-plane compression, the honeycomb exhibits two critical deformation events, i.e., elastic mechanical instability (including elastic buckling and structural transformation) and inelastic structural collapse. The above events were shown to be strongly dependent on the honeycomb cell size and affected by the local atomic bonding at the cell junction. By treating the 3D graphene honeycomb as a continuum cellular solid, and accounting for the structural heterogeneity and constraint at the junction, a set of analytical models were developed to accurately predict the threshold stresses corresponding to the onset of those deformation events. The present study elucidates key structure-property relationships of 3D graphene honeycombs under out-of-plane compression, and provides a comprehensive theoretical framework to predictively analyze their deformation responses, and more generally, offers critical new knowledge for the rational bottom-up design of 3D networks of two-dimensional nanomaterials.

Antibody-protein interactions: benchmark datasets and prediction tools evaluation

PubMed Central

Ponomarenko, Julia V; Bourne, Philip E

2007-01-01

Background The ability to predict antibody binding sites (aka antigenic determinants or B-cell epitopes) for a given protein is a precursor to new vaccine design and diagnostics. Among the various methods of B-cell epitope identification X-ray crystallography is one of the most reliable methods. Using these experimental data computational methods exist for B-cell epitope prediction. As the number of structures of antibody-protein complexes grows, further interest in prediction methods using 3D structure is anticipated. This work aims to establish a benchmark for 3D structure-based epitope prediction methods. Results Two B-cell epitope benchmark datasets inferred from the 3D structures of antibody-protein complexes were defined. The first is a dataset of 62 representative 3D structures of protein antigens with inferred structural epitopes. The second is a dataset of 82 structures of antibody-protein complexes containing different structural epitopes. Using these datasets, eight web-servers developed for antibody and protein binding sites prediction have been evaluated. In no method did performance exceed a 40% precision and 46% recall. The values of the area under the receiver operating characteristic curve for the evaluated methods were about 0.6 for ConSurf, DiscoTope, and PPI-PRED methods and above 0.65 but not exceeding 0.70 for protein-protein docking methods when the best of the top ten models for the bound docking were considered; the remaining methods performed close to random. The benchmark datasets are included as a supplement to this paper. Conclusion It may be possible to improve epitope prediction methods through training on datasets which include only immune epitopes and through utilizing more features characterizing epitopes, for example, the evolutionary conservation score. Notwithstanding, overall poor performance may reflect the generality of antigenicity and hence the inability to decipher B-cell epitopes as an intrinsic feature of the protein. It is an open question as to whether ultimately discriminatory features can be found. PMID:17910770

Evaluation of Fish Passage at Whitewater Parks Using 2D and 3D Hydraulic Modeling

NASA Astrophysics Data System (ADS)

Hardee, T.; Nelson, P. A.; Kondratieff, M.; Bledsoe, B. P.

2016-12-01

In-stream whitewater parks (WWPs) are increasingly popular recreational amenities that typically create waves by constricting flow through a chute to increase velocities and form a hydraulic jump. However, the hydraulic conditions these structures create can limit longitudinal habitat connectivity and potentially inhibit upstream fish migration, especially of native fishes. An improved understanding of the fundamental hydraulic processes and potential environmental effects of whitewater parks is needed to inform management decisions about Recreational In-Channel Diversions (RICDs). Here, we use hydraulic models to compute a continuous and spatially explicit description of velocity and depth along potential fish swimming paths in the flow field, and the ensemble of potential paths are compared to fish swimming performance data to predict fish passage via logistic regression analysis. While 3d models have been shown to accurately predict trout movement through WWP structures, 2d methods can provide a more cost-effective and manager-friendly approach to assessing the effects of similar hydraulic structures on fish passage when 3d analysis in not feasible. Here, we use 2d models to examine the hydraulics in several WWP structures on the North Fork of the St. Vrain River at Lyons, Colorado, and we compare these model results to fish passage predictions from a 3d model. Our analysis establishes a foundation for a practical, transferable and physically-rigorous 2d modeling approach for mechanistically evaluating the effects of hydraulic structures on fish passage.

VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography.

PubMed

Huang, Ruobing; Xie, Weidi; Alison Noble, J

2018-04-23

Three-dimensional (3D) fetal neurosonography is used clinically to detect cerebral abnormalities and to assess growth in the developing brain. However, manual identification of key brain structures in 3D ultrasound images requires expertise to perform and even then is tedious. Inspired by how sonographers view and interact with volumes during real-time clinical scanning, we propose an efficient automatic method to simultaneously localize multiple brain structures in 3D fetal neurosonography. The proposed View-based Projection Networks (VP-Nets), uses three view-based Convolutional Neural Networks (CNNs), to simplify 3D localizations by directly predicting 2D projections of the key structures onto three anatomical views. While designed for efficient use of data and GPU memory, the proposed VP-Nets allows for full-resolution 3D prediction. We investigated parameters that influence the performance of VP-Nets, e.g. depth and number of feature channels. Moreover, we demonstrate that the model can pinpoint the structure in 3D space by visualizing the trained VP-Nets, despite only 2D supervision being provided for a single stream during training. For comparison, we implemented two other baseline solutions based on Random Forest and 3D U-Nets. In the reported experiments, VP-Nets consistently outperformed other methods on localization. To test the importance of loss function, two identical models are trained with binary corss-entropy and dice coefficient loss respectively. Our best VP-Net model achieved prediction center deviation: 1.8 ± 1.4 mm, size difference: 1.9 ± 1.5 mm, and 3D Intersection Over Union (IOU): 63.2 ± 14.7% when compared to the ground truth. To make the whole pipeline intervention free, we also implement a skull-stripping tool using 3D CNN, which achieves high segmentation accuracy. As a result, the proposed processing pipeline takes a raw ultrasound brain image as input, and output a skull-stripped image with five detected key brain structures. Copyright © 2018 Elsevier B.V. All rights reserved.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

PubMed

Nielsen, Morten; Lundegaard, Claus; Lund, Ole; Petersen, Thomas Nordahl

2010-07-01

CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

Structural prediction and analysis of VIH-related peptides from selected crustacean species

PubMed Central

Nagaraju, Ganji Purna Chandra; Kumari, Nunna Siva; Prasad, Ganji Lakshmi Vara; Rajitha, Balney; Meenu, Madan; Rao, Manam Sreenivasa; Naik, Bannoth Reddya

2009-01-01

The tentative elucidation of the 3D-structure of vitellogenesis inhibiting hormone (VIH) peptides is conversely underprivileged by difficulties in gaining enough peptide or protein, diffracting crystals, and numerous extra technical aspects. As a result, no structural information is available for VIH peptide sequences registered in the Genbank. In this situation, it is not surprising that predictive methods have achieved great interest. Here, in this study the molt-inhibiting hormone (MIH) of the kuruma prawn (Marsupenaeus japonicus) is used, to predict the structure of four VIHrelated peptides in the crustacean species. The high similarity of the 3D-structures and the calculated physiochemical characteristics of these peptides suggest a common fold for the entire family. PMID:20011146

FUN3D and CFL3D Computations for the First High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Lee-Rausch, Elizabeth M.; Rumsey, Christopher L.

2011-01-01

Two Reynolds-averaged Navier-Stokes codes were used to compute flow over the NASA Trapezoidal Wing at high lift conditions for the 1st AIAA CFD High Lift Prediction Workshop, held in Chicago in June 2010. The unstructured-grid code FUN3D and the structured-grid code CFL3D were applied to several different grid systems. The effects of code, grid system, turbulence model, viscous term treatment, and brackets were studied. The SST model on this configuration predicted lower lift than the Spalart-Allmaras model at high angles of attack; the Spalart-Allmaras model agreed better with experiment. Neglecting viscous cross-derivative terms caused poorer prediction in the wing tip vortex region. Output-based grid adaptation was applied to the unstructured-grid solutions. The adapted grids better resolved wake structures and reduced flap flow separation, which was also observed in uniform grid refinement studies. Limitations of the adaptation method as well as areas for future improvement were identified.

Automatic analysis for neuron by confocal laser scanning microscope

NASA Astrophysics Data System (ADS)

Satou, Kouhei; Aoki, Yoshimitsu; Mataga, Nobuko; Hensh, Takao K.; Taki, Katuhiko

2005-12-01

The aim of this study is to develop a system that recognizes both the macro- and microscopic configurations of nerve cells and automatically performs the necessary 3-D measurements and functional classification of spines. The acquisition of 3-D images of cranial nerves has been enabled by the use of a confocal laser scanning microscope, although the highly accurate 3-D measurements of the microscopic structures of cranial nerves and their classification based on their configurations have not yet been accomplished. In this study, in order to obtain highly accurate measurements of the microscopic structures of cranial nerves, existing positions of spines were predicted by the 2-D image processing of tomographic images. Next, based on the positions that were predicted on the 2-D images, the positions and configurations of the spines were determined more accurately by 3-D image processing of the volume data. We report the successful construction of an automatic analysis system that uses a coarse-to-fine technique to analyze the microscopic structures of cranial nerves with high speed and accuracy by combining 2-D and 3-D image analyses.

Benchmarking density functional theory predictions of framework structures and properties in a chemically diverse test set of metal-organic frameworks

DOE PAGES

Nazarian, Dalar; Ganesh, P.; Sholl, David S.

2015-09-30

We compiled a test set of chemically and topologically diverse Metal–Organic Frameworks (MOFs) with high accuracy experimentally derived crystallographic structure data. The test set was used to benchmark the performance of Density Functional Theory (DFT) functionals (M06L, PBE, PW91, PBE-D2, PBE-D3, and vdW-DF2) for predicting lattice parameters, unit cell volume, bonded parameters and pore descriptors. On average PBE-D2, PBE-D3, and vdW-DF2 predict more accurate structures, but all functionals predicted pore diameters within 0.5 Å of the experimental diameter for every MOF in the test set. The test set was also used to assess the variance in performance of DFT functionalsmore » for elastic properties and atomic partial charges. The DFT predicted elastic properties such as minimum shear modulus and Young's modulus can differ by an average of 3 and 9 GPa for rigid MOFs such as those in the test set. Moreover, we calculated the partial charges by vdW-DF2 deviate the most from other functionals while there is no significant difference between the partial charges calculated by M06L, PBE, PW91, PBE-D2 and PBE-D3 for the MOFs in the test set. We find that while there are differences in the magnitude of the properties predicted by the various functionals, these discrepancies are small compared to the accuracy necessary for most practical applications.« less

Data-Driven High-Throughput Prediction of the 3D Structure of Small Molecules: Review and Progress

PubMed Central

Andronico, Alessio; Randall, Arlo; Benz, Ryan W.; Baldi, Pierre

2011-01-01

Accurate prediction of the 3D structure of small molecules is essential in order to understand their physical, chemical, and biological properties including how they interact with other molecules. Here we survey the field of high-throughput methods for 3D structure prediction and set up new target specifications for the next generation of methods. We then introduce COSMOS, a novel data-driven prediction method that utilizes libraries of fragment and torsion angle parameters. We illustrate COSMOS using parameters extracted from the Cambridge Structural Database (CSD) by analyzing their distribution and then evaluating the system’s performance in terms of speed, coverage, and accuracy. Results show that COSMOS represents a significant improvement when compared to the state-of-the-art, particularly in terms of coverage of complex molecular structures, including metal-organics. COSMOS can predict structures for 96.4% of the molecules in the CSD [99.6% organic, 94.6% metal-organic] whereas the widely used commercial method CORINA predicts structures for 68.5% [98.5% organic, 51.6% metal-organic]. On the common subset of molecules predicted by both methods COSMOS makes predictions with an average speed per molecule of 0.15s [0.10s organic, 0.21s metal-organic], and an average RMSD of 1.57Å [1.26Å organic, 1.90Å metal-organic], and CORINA makes predictions with an average speed per molecule of 0.13s [0.18s organic, 0.08s metal-organic], and an average RMSD of 1.60Å [1.13Å organic, 2.11Å metal-organic]. COSMOS is available through the ChemDB chemoinformatics web portal at: http://cdb.ics.uci.edu/. PMID:21417267

Evaluation of Shear Strength of RC Beams with Multiple Interfaces Formed before Initial Setting Using 3D Printing Technology

PubMed Central

Kim, Kyeongjin; Park, Sangmin; Jeong, Yoseok; Lee, Jaeha

2017-01-01

With the recent development of 3D printing technology, concrete materials are sometimes used in 3D printing. Concrete structures based on 3D printing have been characterized to have the form of multiple layer build-up. Unlike general concrete structures, therefore, the 3D-printed concrete can be regarded as an orthotropic material. The material property of the 3D-printed concrete’s interface between layers is expected to be far different from that of general concrete bodies since there are no aggregate interlocks and weak chemical bonding. Such a difference finally affects the structural performance of concrete structures even though the interfaces are formed before initial setting of the concrete. The current study mainly reviewed the changes in fracture energy (toughness) with respect to various environmental conditions of such interface. Changes in fracture energies of interfaces between concrete layers were measured using low-speed Crack Mouth Opening Displacement (CMOD) closed loop concrete fracture test. The experimental results indicated reduction in fracture energy as well as tensile strengths. To improve the tensile strength of interfaces, the use of bridging materials is suggested. Since it was assumed that reduction in fracture energy could be a cause of shear strength, to evaluate the reduced structural performance of concrete structure constructed with multiple interfaces by 3D printing technology, the shear strength of RC beam by 3D printing technology was predicted and compared with that of plain RC beam. Based on the fracture energy measured in this study, Modified Compression Field Theory (MCFT) theory-applied Vector 2 program was employed to predict the degree of reduction in shear strength without considering stirrups. Reduction factors were presented based on the obtained results to predict the reduction in shear strength due to interfaces before initial setting of the concrete.

Modeling and simulation studies of human β3 adrenergic receptor and its interactions with agonists.

PubMed

Sahi, Shakti; Tewatia, Parul; Malik, Balwant K

2012-12-01

β3 adrenergic receptor (β3AR) is known to mediate various pharmacological and physiological effects such as thermogenesis in brown adipocytes, lipolysis in white adipocytes, glucose homeostasis and intestinal smooth muscle relaxation. Several efforts have been made in this field to understand their function and regulation in different human tissues and they have emerged as potential attractive targets in drug discovery for the treatment of diabetes, depression, obesity etc. Although the crystal structures of Bovine Rhodopsin and β2 adrenergic receptor have been resolved, to date there is no three dimensional structural information on β3AR. Our aim in this study was to model 3D structure of β3AR by various molecular modeling and simulation techniques. In this paper, we describe a refined predicted model of β3AR using different algorithms for structure prediction. The structural refinement and minimization of the generated 3D model of β3AR were done by Schrodinger suite 9.1. Docking studies of β3AR model with the known agonists enabled us to identify specific residues, viz, Asp 117, Ser 208, Ser 209, Ser 212, Arg 315, Asn 332, within the β3AR binding pocket, which might play an important role in ligand binding. Receptor ligand interaction studies clearly indicated that these five residues showed strong hydrogen bonding interactions with the ligands. The results have been correlated with the experimental data available. The predicted ligand binding interactions and the simulation studies validate the methods used to predict the 3D-structure.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2016-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2017-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

Directing three-dimensional multicellular morphogenesis by self-organization of vascular mesenchymal cells in hyaluronic acid hydrogels.

PubMed

Zhu, Xiaolu; Gojgini, Shiva; Chen, Ting-Hsuan; Fei, Peng; Dong, Siyan; Ho, Chih-Ming; Segura, Tatiana

2017-01-01

Physical scaffolds are useful for supporting cells to form three-dimensional (3D) tissue. However, it is non-trivial to develop a scheme that can robustly guide cells to self-organize into a tissue with the desired 3D spatial structures. To achieve this goal, the rational regulation of cellular self-organization in 3D extracellular matrix (ECM) such as hydrogel is needed. In this study, we integrated the Turing reaction-diffusion mechanism with the self-organization process of cells and produced multicellular 3D structures with the desired configurations in a rational manner. By optimizing the components of the hydrogel and applying exogenous morphogens, a variety of multicellular 3D architectures composed of multipotent vascular mesenchymal cells (VMCs) were formed inside hyaluronic acid (HA) hydrogels. These 3D architectures could mimic the features of trabecular bones and multicellular nodules. Based on the Turing reaction-diffusion instability of morphogens and cells, a theoretical model was proposed to predict the variations observed in 3D multicellular structures in response to exogenous factors. It enabled the feasibility to obtain diverse types of 3D multicellular structures by addition of Noggin and/or BMP2. The morphological consistency between the simulation prediction and experimental results probably revealed a Turing-type mechanism underlying the 3D self-organization of VMCs in HA hydrogels. Our study has provided new ways to create a variety of self-organized 3D multicellular architectures for regenerating biomaterial and tissues in a Turing mechanism-based approach.

Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

PubMed

Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

2017-10-12

Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

Generation of 3D templates of active sites of proteins with rigid prosthetic groups.

PubMed

Nebel, Jean-Christophe

2006-05-15

With the increasing availability of protein structures, the generation of biologically meaningful 3D patterns from the simultaneous alignment of several protein structures is an exciting prospect: active sites could be better understood, protein functions and protein 3D structures could be predicted more accurately. Although patterns can already be generated at the fold and topological levels, no system produces high-resolution 3D patterns including atom and cavity positions. To address this challenge, our research focuses on generating patterns from proteins with rigid prosthetic groups. Since these groups are key elements of protein active sites, the generated 3D patterns are expected to be biologically meaningful. In this paper, we present a new approach which allows the generation of 3D patterns from proteins with rigid prosthetic groups. Using 237 protein chains representing proteins containing porphyrin rings, our method was validated by comparing 3D templates generated from homologues with the 3D structure of the proteins they model. Atom positions were predicted reliably: 93% of them had an accuracy of 1.00 A or less. Moreover, similar results were obtained regarding chemical group and cavity positions. Results also suggested our system could contribute to the validation of 3D protein models. Finally, a 3D template was generated for the active site of human cytochrome P450 CYP17, the 3D structure of which is unknown. Its analysis showed that it is biologically meaningful: our method detected the main patterns of the cytochrome P450 superfamily and the motifs linked to catalytic reactions. The 3D template also suggested the position of a residue, which could be involved in a hydrogen bond with CYP17 substrates and the shape and location of a cavity. Comparisons with independently generated 3D models comforted these hypotheses. Alignment software (Nestor3D) is available at http://www.kingston.ac.uk/~ku33185/Nestor3D.html

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

PubMed Central

Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

2015-01-01

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

Structure, stability, thermodynamic properties, and infrared spectra of the protonated water octamer H(+)(H2O)8.

PubMed

Karthikeyan, S; Park, Mina; Shin, Ilgyou; Kim, Kwang S

2008-10-16

We investigated various two-dimensional (2D) and three-dimensional (3D) structures of H (+)(H 2O) 8, using density functional theory (DFT), Moller-Plesset second-order perturbation theory (MP2), and coupled cluster theory with single, double, and perturbative triple excitations (CCSD(T)). The 3D structure is more stable than the 2D structure at all levels of theory on the Born-Oppenheimer surface. With the zero-point energy (ZPE) correction, the predicted structure varies depending on the level of theory. The DFT employing Becke's three parameters with Lee-Yang-Parr functionals (B3LYP) favors the 2D structure. At the complete basis set (CBS) limit, the MP2 calculation favors the 3D structure by 0.29 kcal/mol, and the CCSD(T) calculation favors the 3D structure by 0.27 kcal/mol. It is thus expected that both 2D and 3D structures are nearly isoenergetic near 0 K. At 100 K, all the calculations show that the 2D structure is much more stable in free binding energy than the 3D structure. The DFT and MP2 vibrational spectra of the 2D structure are consistent with the experimental spectra. First-principles Car-Parrinello molecular dynamics (CPMD) simulations show that the 2D Zundel-type vibrational spectra are in good agreement with the experiment.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress. A response to the letter by the Cambridge Crystallographic Data Centre.

PubMed

Baldi, Pierre

2011-12-27

A response is presented to sentiments expressed in "Data-Driven High-Throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. A Response from The Cambridge Crystallographic Data Centre", recently published in the Journal of Chemical Information and Modeling, (1) which may give readers a misleading impression regarding significant impediments to scientific research posed by the CCDC.

F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly.

PubMed

Jain, Swati; Schlick, Tamar

2017-11-24

Coarse-grained models represent attractive approaches to analyze and simulate ribonucleic acid (RNA) molecules, for example, for structure prediction and design, as they simplify the RNA structure to reduce the conformational search space. Our structure prediction protocol RAGTOP (RNA-As-Graphs Topology Prediction) represents RNA structures as tree graphs and samples graph topologies to produce candidate graphs. However, for a more detailed study and analysis, construction of atomic from coarse-grained models is required. Here we present our graph-based fragment assembly algorithm (F-RAG) to convert candidate three-dimensional (3D) tree graph models, produced by RAGTOP into atomic structures. We use our related RAG-3D utilities to partition graphs into subgraphs and search for structurally similar atomic fragments in a data set of RNA 3D structures. The fragments are edited and superimposed using common residues, full atomic models are scored using RAGTOP's knowledge-based potential, and geometries of top scoring models is optimized. To evaluate our models, we assess all-atom RMSDs and Interaction Network Fidelity (a measure of residue interactions) with respect to experimentally solved structures and compare our results to other fragment assembly programs. For a set of 50 RNA structures, we obtain atomic models with reasonable geometries and interactions, particularly good for RNAs containing junctions. Additional improvements to our protocol and databases are outlined. These results provide a good foundation for further work on RNA structure prediction and design applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three-dimensional mapping of soil chemical characteristics at micrometric scale: Statistical prediction by combining 2D SEM-EDX data and 3D X-ray computed micro-tomographic images

NASA Astrophysics Data System (ADS)

Hapca, Simona

2015-04-01

Many soil properties and functions emerge from interactions of physical, chemical and biological processes at microscopic scales, which can be understood only by integrating techniques that traditionally are developed within separate disciplines. While recent advances in imaging techniques, such as X-ray computed tomography (X-ray CT), offer the possibility to reconstruct the 3D physical structure at fine resolutions, for the distribution of chemicals in soil, existing methods, based on scanning electron microscope (SEM) and energy dispersive X-ray detection (EDX), allow for characterization of the chemical composition only on 2D surfaces. At present, direct 3D measurement techniques are still lacking, sequential sectioning of soils, followed by 2D mapping of chemical elements and interpolation to 3D, being an alternative which is explored in this study. Specifically, we develop an integrated experimental and theoretical framework which combines 3D X-ray CT imaging technique with 2D SEM-EDX and use spatial statistics methods to map the chemical composition of soil in 3D. The procedure involves three stages 1) scanning a resin impregnated soil cube by X-ray CT, followed by precision cutting to produce parallel thin slices, the surfaces of which are scanned by SEM-EDX, 2) alignment of the 2D chemical maps within the internal 3D structure of the soil cube, and 3) development, of spatial statistics methods to predict the chemical composition of 3D soil based on the observed 2D chemical and 3D physical data. Specifically, three statistical models consisting of a regression tree, a regression tree kriging and cokriging model were used to predict the 3D spatial distribution of carbon, silicon, iron and oxygen in soil, these chemical elements showing a good spatial agreement between the X-ray grayscale intensities and the corresponding 2D SEM-EDX data. Due to the spatial correlation between the physical and chemical data, the regression-tree model showed a great potential in predicting chemical composition in particular for iron, which is generally sparsely distributed in soil. For carbon, silicon and oxygen, which are more densely distributed, the additional kriging of the regression tree residuals improved significantly the prediction, whereas prediction based on co-kriging was less consistent across replicates, underperforming regression-tree kriging. The present study shows a great potential in integrating geo-statistical methods with imaging techniques to unveil the 3D chemical structure of soil at very fine scales, the framework being suitable to be further applied to other types of imaging data such as images of biological thin sections for characterization of microbial distribution. Key words: X-ray CT, SEM-EDX, segmentation techniques, spatial correlation, 3D soil images, 2D chemical maps.

RNA 3D Structure Modeling by Combination of Template-Based Method ModeRNA, Template-Free Folding with SimRNA, and Refinement with QRNAS.

PubMed

Piatkowski, Pawel; Kasprzak, Joanna M; Kumar, Deepak; Magnus, Marcin; Chojnowski, Grzegorz; Bujnicki, Janusz M

2016-01-01

RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/ . SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb . For model optimization we use QRNAS, available at http://genesilico.pl/qrnas .

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

PubMed Central

Zhao, Manman; Zheng, Linfeng; Qiu, Chun

2017-01-01

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR. PMID:28630865

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

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

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

PubMed

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Secondary structure prediction for complete rDNA sequences (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, and comparison of divergent domains structures across Acari.

PubMed

Zhao, Ya-E; Wang, Zheng-Hang; Xu, Yang; Wu, Li-Ping; Hu, Li

2013-10-01

According to base pairing, the rRNA folds into corresponding secondary structures, which contain additional phylogenetic information. On the basis of sequencing for complete rDNA sequences (18S, ITS1, 5.8S, ITS2 and 28S rDNA) of Demodex, we predicted the secondary structure of the complete rDNA sequence (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, which was in concordance with that of the main arthropod lineages in past studies. And together with the sequence data from GenBank, we also predicted the secondary structures of divergent domains in SSU rRNA of 51 species and in LSU rRNA of 43 species from four superfamilies in Acari (Cheyletoidea, Tetranychoidea, Analgoidea and Ixodoidea). The multiple alignment among the four superfamilies in Acari showed that, insertions from Tetranychoidea SSU rRNA formed two newly proposed helixes, and helix c3-2b of LSU rRNA was absent in Demodex (Cheyletoidea) taxa. Generally speaking, LSU rRNA presented more remarkable differences than SSU rRNA did, mainly in D2, D3, D5, D7a, D7b, D8 and D10. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

Conservation of Three-Dimensional Helix-Loop-Helix Structure through the Vertebrate Lineage Reopens the Cold Case of Gonadotropin-Releasing Hormone-Associated Peptide.

PubMed

Pérez Sirkin, Daniela I; Lafont, Anne-Gaëlle; Kamech, Nédia; Somoza, Gustavo M; Vissio, Paula G; Dufour, Sylvie

2017-01-01

GnRH-associated peptide (GAP) is the C-terminal portion of the gonadotropin-releasing hormone (GnRH) preprohormone. Although it was reported in mammals that GAP may act as a prolactin-inhibiting factor and can be co-secreted with GnRH into the hypophyseal portal blood, GAP has been practically out of the research circuit for about 20 years. Comparative studies highlighted the low conservation of GAP primary amino acid sequences among vertebrates, contributing to consider that this peptide only participates in the folding or carrying process of GnRH. Considering that the three-dimensional (3D) structure of a protein may define its function, the aim of this study was to evaluate if GAP sequences and 3D structures are conserved in the vertebrate lineage. GAP sequences from various vertebrates were retrieved from databases. Analysis of primary amino acid sequence identity and similarity, molecular phylogeny, and prediction of 3D structures were performed. Amino acid sequence comparison and phylogeny analyses confirmed the large variation of GAP sequences throughout vertebrate radiation. In contrast, prediction of the 3D structure revealed a striking conservation of the 3D structure of GAP1 (GAP associated with the hypophysiotropic type 1 GnRH), despite low amino acid sequence conservation. This GAP1 peptide presented a typical helix-loop-helix (HLH) structure in all the vertebrate species analyzed. This HLH structure could also be predicted for GAP2 in some but not all vertebrate species and in none of the GAP3 analyzed. These results allowed us to infer that selective pressures have maintained GAP1 HLH structure throughout the vertebrate lineage. The conservation of the HLH motif, known to confer biological activity to various proteins, suggests that GAP1 peptides may exert some hypophysiotropic biological functions across vertebrate radiation.

Conservation of Three-Dimensional Helix-Loop-Helix Structure through the Vertebrate Lineage Reopens the Cold Case of Gonadotropin-Releasing Hormone-Associated Peptide

PubMed Central

Pérez Sirkin, Daniela I.; Lafont, Anne-Gaëlle; Kamech, Nédia; Somoza, Gustavo M.; Vissio, Paula G.; Dufour, Sylvie

2017-01-01

GnRH-associated peptide (GAP) is the C-terminal portion of the gonadotropin-releasing hormone (GnRH) preprohormone. Although it was reported in mammals that GAP may act as a prolactin-inhibiting factor and can be co-secreted with GnRH into the hypophyseal portal blood, GAP has been practically out of the research circuit for about 20 years. Comparative studies highlighted the low conservation of GAP primary amino acid sequences among vertebrates, contributing to consider that this peptide only participates in the folding or carrying process of GnRH. Considering that the three-dimensional (3D) structure of a protein may define its function, the aim of this study was to evaluate if GAP sequences and 3D structures are conserved in the vertebrate lineage. GAP sequences from various vertebrates were retrieved from databases. Analysis of primary amino acid sequence identity and similarity, molecular phylogeny, and prediction of 3D structures were performed. Amino acid sequence comparison and phylogeny analyses confirmed the large variation of GAP sequences throughout vertebrate radiation. In contrast, prediction of the 3D structure revealed a striking conservation of the 3D structure of GAP1 (GAP associated with the hypophysiotropic type 1 GnRH), despite low amino acid sequence conservation. This GAP1 peptide presented a typical helix-loop-helix (HLH) structure in all the vertebrate species analyzed. This HLH structure could also be predicted for GAP2 in some but not all vertebrate species and in none of the GAP3 analyzed. These results allowed us to infer that selective pressures have maintained GAP1 HLH structure throughout the vertebrate lineage. The conservation of the HLH motif, known to confer biological activity to various proteins, suggests that GAP1 peptides may exert some hypophysiotropic biological functions across vertebrate radiation. PMID:28878737

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures.

PubMed

Solomon, Oz; Kunik, Vered; Simon, Amos; Kol, Nitzan; Barel, Ortal; Lev, Atar; Amariglio, Ninette; Somech, Raz; Rechavi, Gidi; Eyal, Eran

2016-08-26

Evaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates. We present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D . G23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Magnetism in curved geometries

NASA Astrophysics Data System (ADS)

Streubel, Robert

Deterministically bending and twisting two-dimensional structures in the three-dimensional (3D) space provide means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape. The recent developments of 3D curved magnetic geometries, ranging from theoretical predictions over fabrication to characterization using integral means as well as advanced magnetic tomography, will be reviewed. Theoretical works predict a curvature-induced effective anisotropy and effective Dzyaloshinskii-Moriya interaction resulting in a vast of novel effects including magnetochiral effects (chirality symmetry breaking) and topologically induced magnetization patterning. The remarkable development of nanotechnology, e.g. preparation of high-quality extended thin films, nanowires and frameworks via chemical and physical deposition as well as 3D nano printing, has granted first insights into the fundamental properties of 3D shaped magnetic objects. Optimizing magnetic and structural properties of these novel 3D architectures demands new investigation methods, particularly those based on vector tomographic imaging. Magnetic neutron tomography and electron-based 3D imaging, such as electron holography and vector field electron tomography, are well-established techniques to investigate macroscopic and nanoscopic samples, respectively. At the mesoscale, the curved objects can be investigated using the novel method of magnetic X-ray tomography. In spite of experimental challenges to address the appealing theoretical predictions of curvature-induced effects, those 3D magnetic architectures have already proven their application potential for life sciences, targeted delivery, realization of 3D spin-wave filters, and magneto-encephalography devices, to name just a few. DOE BES MSED (DE-AC02-05-CH11231).

Alignment-independent technique for 3D QSAR analysis

NASA Astrophysics Data System (ADS)

Wilkes, Jon G.; Stoyanova-Slavova, Iva B.; Buzatu, Dan A.

2016-04-01

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test 2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test 2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test 2 = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.

CAD-Based Modeling of Advanced Rotary Wing Structures for Integrated 3-D Aeromechanics Analysis

NASA Astrophysics Data System (ADS)

Staruk, William

This dissertation describes the first comprehensive use of integrated 3-D aeromechanics modeling, defined as the coupling of 3-D solid finite element method (FEM) structural dynamics with 3-D computational fluid dynamics (CFD), for the analysis of a real helicopter rotor. The development of this new methodology (a departure from how rotor aeroelastic analysis has been performed for 40 years), its execution on a real rotor, and the fundamental understanding of aeromechanics gained from it, are the key contributions of this dissertation. This work also presents the first CFD/CSD analysis of a tiltrotor in edgewise flight, revealing many of its unique loading mechanisms. The use of 3-D FEM, integrated with a trim solver and aerodynamics modeling, has the potential to enhance the design of advanced rotors by overcoming fundamental limitations of current generation beam-based analysis tools and offering integrated internal dynamic stress and strain predictions for design. Two primary goals drove this research effort: 1) developing a methodology to create 3-D CAD-based brick finite element models of rotors including multibody joints, controls, and aerodynamic interfaces, and 2) refining X3D, the US Army's next generation rotor structural dynamics solver featuring 3-D FEM within a multibody formulation with integrated aerodynamics, to model a tiltrotor in the edgewise conversion flight regime, which drives critical proprotor structural loads. Prior tiltrotor analysis has primarily focused on hover aerodynamics with rigid blades or forward flight whirl-flutter stability with simplified aerodynamics. The first goal was met with the development of a detailed methodology for generating multibody 3-D structural models, starting from CAD geometry, continuing to higher-order hexahedral finite element meshing, to final assembly of the multibody model by creating joints, assigning material properties, and defining the aerodynamic interface. Several levels of verification and validation were carried out systematically, covering formulation, model accuracy, and accuracy of the physics of the problem and the many complex coupled aeromechanical phenomena that characterize the behavior of a tiltrotor in the conversion corridor. Compatibility of the new structural analysis models with X3D is demonstrated using analytical test cases, including 90° twisted beams and thick composite plates, and a notional bearingless rotor. Prediction of deformations and stresses in composite beams and plates is validated and verified against experimental measurements, theory, and state-of-the-art beam models. The second goal was met through integrated analysis of the Tilt Rotor Aeroacoustic Model (TRAM) proprotor using X3D coupled to Helios--the US Army's next generation CFD framework featuring a high fidelity Reynolds-average Navier-Stokes (RANS) structured/unstructured overset solver--as well as low order aerodynamic models. Although development of CFD was not part of this work, coupling X3D with Helios was, including establishing consistent interface definitions for blade deformations (for CFD mesh motion), aerodynamic interfaces (for loads transfer), and rotor control angles (for trim). It is expected that this method and solver will henceforth be an integral part of the Helios framework, providing an equal fidelity of representation for fluids and structures in the development of future advanced rotor systems. Structural dynamics analysis of the TRAM model show accurate prediction of the lower natural frequencies, demonstrating the ability to model advanced rotors from first principles using 3-D structural dynamics, and a study of how joint properties affect these frequencies reveals how X3D can be used as a detailed design tool. The CFD/CSD analysis reveals accurate prediction of rotor performance and airloads in edgewise flight when compared to wind tunnel test data. Structural blade loads trends are well predicted at low thrust, but a 3/rev component of flap and lag bending moment appearing in test data at high thrust remains a mystery. Efficiently simulating a gimbaled rotor is not trivial; a time-domain method with only a single blade model is proposed and tested. The internal stress in the blade, particularly at its root where the gimbal action has major influence, is carefully examined, revealing complex localized loading patterns.

Beyond small molecule SAR – using the dopamine D3 receptor crystal structure to guide drug design

PubMed Central

Keck, Thomas M.; Burzynski, Caitlin; Shi, Lei; Newman, Amy Hauck

2016-01-01

The dopamine D3 receptor is a target of pharmacotherapeutic interest in a variety of neurological disorders including schizophrenia, restless leg syndrome, and drug addiction. The high protein sequence homology between the D3 and D2 receptors has posed a challenge to developing D3 receptor-selective ligands whose behavioral actions can be attributed to D3 receptor engagement, in vivo. However, through primarily small molecule structure-activity relationship (SAR) studies, a variety of chemical scaffolds have been discovered over the past two decades that have resulted in several D3 receptor-selective ligands with high affinity and in vivo activity. Nevertheless, viable clinical candidates remain limited. The recent determination of the high-resolution crystal structure of the D3 receptor has invigorated structure-based drug design, providing refinements to the molecular dynamic models and testable predictions about receptor-ligand interactions. This review will highlight recent preclinical and clinical studies demonstrating potential utility of D3 receptor-selective ligands in the treatment of addiction. In addition, new structure-based rational drug design strategies for D3 receptor-selective ligands that complement traditional small molecule SAR to improve the selectivity and directed efficacy profiles are examined. PMID:24484980

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

A Novel Quasi-3D Method for Cascade Flow Considering Axial Velocity Density Ratio

NASA Astrophysics Data System (ADS)

Chen, Zhiqiang; Zhou, Ming; Xu, Quanyong; Huang, Xudong

2018-03-01

A novel quasi-3D Computational Fluid Dynamics (CFD) method of mid-span flow simulation for compressor cascades is proposed. Two dimension (2D) Reynolds-Averaged Navier-Stokes (RANS) method is shown facing challenge in predicting mid-span flow with a unity Axial Velocity Density Ratio (AVDR). Three dimension (3D) RANS solution also shows distinct discrepancies if the AVDR is not predicted correctly. In this paper, 2D and 3D CFD results discrepancies are analyzed and a novel quasi-3D CFD method is proposed. The new quasi-3D model is derived by reducing 3D RANS Finite Volume Method (FVM) discretization over a one-spanwise-layer structured mesh cell. The sidewall effect is considered by two parts. The first part is explicit interface fluxes of mass, momentum and energy as well as turbulence. The second part is a cell boundary scaling factor representing sidewall boundary layer contraction. The performance of the novel quasi-3D method is validated on mid-span pressure distribution, pressure loss and shock prediction of two typical cascades. The results show good agreement with the experiment data on cascade SJ301-20 and cascade AC6-10 at all test condition. The proposed quasi-3D method shows superior accuracy over traditional 2D RANS method and 3D RANS method in performance prediction of compressor cascade.

Hyperfine structure of electronic levels and the first measurement of the nuclear magnetic moment of 63Ni

NASA Astrophysics Data System (ADS)

D'yachkov, A. B.; Firsov, V. A.; Gorkunov, A. A.; Labozin, A. V.; Mironov, S. M.; Saperstein, E. E.; Tolokonnikov, S. V.; Tsvetkov, G. O.; Panchenko, V. Y.

2017-01-01

Laser resonant photoionization spectroscopy was used to study the hyperfine structure of the optical 3d84s2 {}3F4→ 3d84s4p {}3G^o3 and 3d94s {}3D3→ 3d84s4p {}3G^o3 transitions of 63Ni and 61Ni isotopes. Experimental spectra allowed us to derive hyperfine interaction constants and determine the magnetic dipole moment of the nuclear ground state of 63Ni for the first time: μ=+0.496(5)μ_N. The value obtained agrees well with the prediction of the self-consistent theory of finite Fermi systems.

Polymer physics predicts the effects of structural variants on chromatin architecture.

PubMed

Bianco, Simona; Lupiáñez, Darío G; Chiariello, Andrea M; Annunziatella, Carlo; Kraft, Katerina; Schöpflin, Robert; Wittler, Lars; Andrey, Guillaume; Vingron, Martin; Pombo, Ana; Mundlos, Stefan; Nicodemi, Mario

2018-05-01

Structural variants (SVs) can result in changes in gene expression due to abnormal chromatin folding and cause disease. However, the prediction of such effects remains a challenge. Here we present a polymer-physics-based approach (PRISMR) to model 3D chromatin folding and to predict enhancer-promoter contacts. PRISMR predicts higher-order chromatin structure from genome-wide chromosome conformation capture (Hi-C) data. Using the EPHA4 locus as a model, the effects of pathogenic SVs are predicted in silico and compared to Hi-C data generated from mouse limb buds and patient-derived fibroblasts. PRISMR deconvolves the folding complexity of the EPHA4 locus and identifies SV-induced ectopic contacts and alterations of 3D genome organization in homozygous or heterozygous states. We show that SVs can reconfigure topologically associating domains, thereby producing extensive rewiring of regulatory interactions and causing disease by gene misexpression. PRISMR can be used to predict interactions in silico, thereby providing a tool for analyzing the disease-causing potential of SVs.

Structural insights into conserved L-arabinose metabolic enzymes reveal the substrate binding site of a thermophilic L-arabinose isomerase.

PubMed

Lee, Yong-Jik; Lee, Sang-Jae; Kim, Seong-Bo; Lee, Sang Jun; Lee, Sung Haeng; Lee, Dong-Woo

2014-03-18

Structural genomics demonstrates that despite low levels of structural similarity of proteins comprising a metabolic pathway, their substrate binding regions are likely to be conserved. Herein based on the 3D-structures of the α/β-fold proteins involved in the ara operon, we attempted to predict the substrate binding residues of thermophilic Geobacillus stearothermophilus L-arabinose isomerase (GSAI) with no 3D-structure available. Comparison of the structures of L-arabinose catabolic enzymes revealed a conserved feature to form the substrate-binding modules, which can be extended to predict the substrate binding site of GSAI (i.e., D195, E261 and E333). Moreover, these data implicated that proteins in the l-arabinose metabolic pathway might retain their substrate binding niches as the modular structure through conserved molecular evolution even with totally different structural scaffolds. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Improved pose and affinity predictions using different protocols tailored on the basis of data availability

NASA Astrophysics Data System (ADS)

Prathipati, Philip; Nagao, Chioko; Ahmad, Shandar; Mizuguchi, Kenji

2016-09-01

The D3R 2015 grand drug design challenge provided a set of blinded challenges for evaluating the applicability of our protocols for pose and affinity prediction. In the present study, we report the application of two different strategies for the two D3R protein targets HSP90 and MAP4K4. HSP90 is a well-studied target system with numerous co-crystal structures and SAR data. Furthermore the D3R HSP90 test compounds showed high structural similarity to existing HSP90 inhibitors in BindingDB. Thus, we adopted an integrated docking and scoring approach involving a combination of both pharmacophoric and heavy atom similarity alignments, local minimization and quantitative structure activity relationships modeling, resulting in the reasonable prediction of pose [with the root mean square deviation (RMSD) values of 1.75 Å for mean pose 1, 1.417 Å for the mean best pose and 1.85 Å for the mean all poses] and affinity (ROC AUC = 0.702 at 7.5 pIC50 cut-off and R = 0.45 for 180 compounds). The second protein, MAP4K4, represents a novel system with limited SAR and co-crystal structure data and little structural similarity of the D3R MAP4K4 test compounds to known MAP4K4 ligands. For this system, we implemented an exhaustive pose and affinity prediction protocol involving docking and scoring using the PLANTS software which considers side chain flexibility together with protein-ligand fingerprints analysis assisting in pose prioritization. This protocol through fares poorly in pose prediction (with the RMSD values of 4.346 Å for mean pose 1, 4.69 Å for mean best pose and 4.75 Å for mean all poses) and produced reasonable affinity prediction (AUC = 0.728 at 7.5 pIC50 cut-off and R = 0.67 for 18 compounds, ranked 1st among 80 submissions).

The Value of 3D Printing Models of Left Atrial Appendage Using Real-Time 3D Transesophageal Echocardiographic Data in Left Atrial Appendage Occlusion: Applications toward an Era of Truly Personalized Medicine.

PubMed

Liu, Peng; Liu, Rijing; Zhang, Yan; Liu, Yingfeng; Tang, Xiaoming; Cheng, Yanzhen

The objective of this study was to assess the clinical feasibility of generating 3D printing models of left atrial appendage (LAA) using real-time 3D transesophageal echocardiogram (TEE) data for preoperative reference of LAA occlusion. Percutaneous LAA occlusion can effectively prevent patients with atrial fibrillation from stroke. However, the anatomical structure of LAA is so complicated that adequate information of its structure is essential for successful LAA occlusion. Emerging 3D printing technology has the demonstrated potential to structure more accurately than conventional imaging modalities by creating tangible patient-specific models. Typically, 3D printing data sets are acquired from CT and MRI, which may involve intravenous contrast, sedation, and ionizing radiation. It has been reported that 3D models of LAA were successfully created by the data acquired from CT. However, 3D printing of the LAA using real-time 3D TEE data has not yet been explored. Acquisition of 3D transesophageal echocardiographic data from 8 patients with atrial fibrillation was performed using the Philips EPIQ7 ultrasound system. Raw echocardiographic image data were opened in Philips QLAB and converted to 'Cartesian DICOM' format and imported into Mimics® software to create 3D models of LAA, which were printed using a rubber-like material. The printed 3D models were then used for preoperative reference and procedural simulation in LAA occlusion. We successfully printed LAAs of 8 patients. Each LAA costs approximately CNY 800-1,000 and the total process takes 16-17 h. Seven of the 8 Watchman devices predicted by preprocedural 2D TEE images were of the same sizes as those placed in the real operation. Interestingly, 3D printing models were highly reflective of the shape and size of LAAs, and all device sizes predicted by the 3D printing model were fully consistent with those placed in the real operation. Also, the 3D printed model could predict operating difficulty and the presence of a peridevice leak. 3D printing of the LAA using real-time 3D transesophageal echocardiographic data has a perfect and rapid application in LAA occlusion to assist with physician planning and decision making. © 2016 S. Karger AG, Basel.

Tests of Predictions of the Algebraic Cluster Model: the Triangular D 3h Symmetry of 12C

NASA Astrophysics Data System (ADS)

Gai, Moshe

2016-07-01

A new theoretical approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts rotation-vibration structure with rotational band of an oblate equilateral triangular symmetric spinning top with a D 3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with a degenerate 4+ and 4- (parity doublet) states. Our measured new 2+ 2 in 12C allows the first study of rotation-vibration structure in 12C. The newly measured 5- state and 4- states fit very well the predicted ground state rotational band structure with the predicted sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a D 3h symmetry is characteristic of triatomic molecules, but it is observed in the ground state rotational band of 12C for the first time in a nucleus. We discuss predictions of the ACM of other rotation-vibration bands in 12 C such as the (0+) Hoyle band and the (1-) bending mode with prediction of (“missing 3- and 4-”) states that may shed new light on clustering in 12C and light nuclei. In particular, the observation (or non observation) of the predicted (“missing”) states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.6542 MeV in 12C. We discuss proposed research programs at the Darmstadt S-DALINAC and at the newly constructed ELI-NP facility near Bucharest to test the predictions of the ACM in isotopes of carbon.

RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

PubMed Central

Cruz, José Almeida; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cao, Song; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Flores, Samuel Coulbourn; Huang, Lili; Lavender, Christopher A.; Lisi, Véronique; Major, François; Mikolajczak, Katarzyna; Patel, Dinshaw J.; Philips, Anna; Puton, Tomasz; Santalucia, John; Sijenyi, Fredrick; Hermann, Thomas; Rother, Kristian; Rother, Magdalena; Serganov, Alexander; Skorupski, Marcin; Soltysinski, Tomasz; Sripakdeevong, Parin; Tuszynska, Irina; Weeks, Kevin M.; Waldsich, Christina; Wildauer, Michael; Leontis, Neocles B.; Westhof, Eric

2012-01-01

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises. PMID:22361291

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1994-10-15

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-12-31

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Engineering 3D Models of Tumors and Bone to Understand Tumor-Induced Bone Disease and Improve Treatments.

PubMed

Kwakwa, Kristin A; Vanderburgh, Joseph P; Guelcher, Scott A; Sterling, Julie A

2017-08-01

Bone is a structurally unique microenvironment that presents many challenges for the development of 3D models for studying bone physiology and diseases, including cancer. As researchers continue to investigate the interactions within the bone microenvironment, the development of 3D models of bone has become critical. 3D models have been developed that replicate some properties of bone, but have not fully reproduced the complex structural and cellular composition of the bone microenvironment. This review will discuss 3D models including polyurethane, silk, and collagen scaffolds that have been developed to study tumor-induced bone disease. In addition, we discuss 3D printing techniques used to better replicate the structure of bone. 3D models that better replicate the bone microenvironment will help researchers better understand the dynamic interactions between tumors and the bone microenvironment, ultimately leading to better models for testing therapeutics and predicting patient outcomes.

High-pressure phase transitions of nitinol NiTi to a semiconductor with an unusual topological structure

NASA Astrophysics Data System (ADS)

Liu, Guangtao; Liu, Hanyu; Feng, Xiaolei; Redfern, Simon A. T.

2018-04-01

Systematic ab initio structure simulations have been used to explore the high-pressure behavior of nitinol (NiTi) at zero temperature. Our crystal structure prediction and first-principles calculations reveal that the known B 19 phase is dynamically unstable, and an orthorhombic structure (Pbcm) and a face-centered-cubic B 32 structure (F d 3 ¯m ) become stable above ˜4 and 29 GPa, respectively. The predicted, highest-pressure, B 32 phase is composed of two interpenetrating diamond structures, with a structural topology that is quite distinct from that of the other phases of NiTi. Interestingly, the B 32 phase shows an unusual semiconducting characteristic as a result of its unique band structure and the nature of 3 d orbitals localization, whose expected synthesis pressure is accessible to current experimental techniques.

Prediction of the bottomonium D-wave spectrum from full lattice QCD.

PubMed

Daldrop, J O; Davies, C T H; Dowdall, R J

2012-03-09

We calculate the full spectrum of D-wave states in the Υ system in lattice QCD for the first time, by using an improved version of nonrelativistic QCD on coarse and fine "second-generation" gluon field configurations from the MILC Collaboration that include the effect of up, down, strange, and charm quarks in the sea. By taking the 2S-1S splitting to set the lattice spacing, we determine the (3)D2-1S splitting to 2.3% and find agreement with experiment. Our prediction of the fine structure relative to the (3)D2 gives the (3)D3 at 10.181(5) GeV and the (3)D1 at 10.147(6) GeV. We also discuss the overlap of (3)D1 operators with (3)S1 states.

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

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.

A constraint logic programming approach to associate 1D and 3D structural components for large protein complexes.

PubMed

Dal Palù, Alessandro; Pontelli, Enrico; He, Jing; Lu, Yonggang

2007-01-01

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and alpha-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

A cross docking pipeline for improving pose prediction and virtual screening performance

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

Grid-Adapted FUN3D Computations for the Second High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Park, M. A.

2014-01-01

Contributions of the unstructured Reynolds-averaged Navier-Stokes code FUN3D to the 2nd AIAA CFD High Lift Prediction Workshop are described, and detailed comparisons are made with experimental data. Using workshop-supplied grids, results for the clean wing configuration are compared with results from the structured code CFL3D Using the same turbulence model, both codes compare reasonably well in terms of total forces and moments, and the maximum lift is similarly over-predicted for both codes compared to experiment. By including more representative geometry features such as slat and flap brackets and slat pressure tube bundles, FUN3D captures the general effects of the Reynolds number variation, but under-predicts maximum lift on workshop-supplied grids in comparison with the experimental data, due to excessive separation. However, when output-based, off-body grid adaptation in FUN3D is employed, results improve considerably. In particular, when the geometry includes both brackets and the pressure tube bundles, grid adaptation results in a more accurate prediction of lift near stall in comparison with the wind-tunnel data. Furthermore, a rotation-corrected turbulence model shows improved pressure predictions on the outboard span when using adapted grids.

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method

NASA Astrophysics Data System (ADS)

Hogues, Hervé; Sulea, Traian; Gaudreault, Francis; Corbeil, Christopher R.; Purisima, Enrico O.

2018-01-01

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau 0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.

Structured Light-Based 3D Reconstruction System for Plants.

PubMed

Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

2015-07-29

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

Response of corrugated fiberboard to moisture flow : a 3-D finite element transient nonlinear analysis

Treesearch

Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid

2003-01-01

Collapse of fiberboard packaging boxes, in the shipping industry, due to rise in humidity conditions is common and very costly. A 3D FE nonlinear model is developed to predict the moisture flow throughout a corrugated packaging fiberboard sandwich structure. The model predicts how the moisture diffusion will permeate through the layers of a fiberboard (medium and...

Inferences from structural comparison: flexibility, secondary structure wobble and sequence alignment optimization.

PubMed

Zhang, Gaihua; Su, Zhen

2012-01-01

Work on protein structure prediction is very useful in biological research. To evaluate their accuracy, experimental protein structures or their derived data are used as the 'gold standard'. However, as proteins are dynamic molecular machines with structural flexibility such a standard may be unreliable. To investigate the influence of the structure flexibility, we analysed 3,652 protein structures of 137 unique sequences from 24 protein families. The results showed that (1) the three-dimensional (3D) protein structures were not rigid: the root-mean-square deviation (RMSD) of the backbone Cα of structures with identical sequences was relatively large, with the average of the maximum RMSD from each of the 137 sequences being 1.06 Å; (2) the derived data of the 3D structure was not constant, e.g. the highest ratio of the secondary structure wobble site was 60.69%, with the sequence alignments from structural comparisons of two proteins in the same family sometimes being completely different. Proteins may have several stable conformations and the data derived from resolved structures as a 'gold standard' should be optimized before being utilized as criteria to evaluate the prediction methods, e.g. sequence alignment from structural comparison. Helix/β-sheet transition exists in normal free proteins. The coil ratio of the 3D structure could affect its resolution as determined by X-ray crystallography.

TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.

PubMed Central

Wallace, A. C.; Borkakoti, N.; Thornton, J. M.

1997-01-01

It is well established that sequence templates such as those in the PROSITE and PRINTS databases are powerful tools for predicting the biological function and tertiary structure for newly derived protein sequences. The number of X-ray and NMR protein structures is increasing rapidly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatically derives 3D templates from structures deposited in the Brookhaven Protein Data Bank. While a new sequence can be searched for sequence patterns, a new structure can be scanned against these 3D templates to identify functional sites. As examples, 3D templates are derived for enzymes with an O-His-O "catalytic triad" and for the ribonucleases and lysozymes. When these 3D templates are applied to a large data set of nonidentical proteins, several interesting hits are located. This suggests that the development of a 3D template database may help to identify the function of new protein structures, if unknown, as well as to design proteins with specific functions. PMID:9385633

Identifying novel sequence variants of RNA 3D motifs

PubMed Central

Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

2015-01-01

Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723

Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study

NASA Astrophysics Data System (ADS)

Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Montes, Matthieu

2018-01-01

The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.

QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

NASA Astrophysics Data System (ADS)

Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

Structure and electronic properties of azadirachtin.

PubMed

de Castro, Elton A S; de Oliveira, Daniel A B; Farias, Sergio A S; Gargano, Ricardo; Martins, João B L

2014-02-01

We performed a combined DFT and Monte Carlo (13)C NMR chemical-shift study of azadirachtin A, a triterpenoid that acts as a natural insect antifeedant. A conformational search using a Monte Carlo technique based on the RM1 semiempirical method was carried out in order to establish its preferred structure. The B3LYP/6-311++G(d,p), wB97XD/6-311++G(d,p), M06/6-311++G(d,p), M06-2X/6-311++G(d,p), and CAM-B3LYP/6-311++G(d,p) levels of theory were used to predict NMR chemical shifts. A Monte Carlo population-weighted average spectrum was produced based on the predicted Boltzmann contributions. In general, good agreement between experimental and theoretical data was obtained using both methods, and the (13)C NMR chemical shifts were predicted highly accurately. The geometry was optimized at the semiempirical level and used to calculate the NMR chemical shifts at the DFT level, and these shifts showed only minor deviations from those obtained following structural optimization at the DFT level, and incurred a much lower computational cost. The theoretical ultraviolet spectrum showed a maximum absorption peak that was mainly contributed by the tiglate group.

Homology modeling a fast tool for drug discovery: current perspectives.

PubMed

Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

PubMed Central

Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

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.

Development of an Evolutionary Algorithm for the ab Initio Discovery of Two-Dimensional Materials

NASA Astrophysics Data System (ADS)

Revard, Benjamin Charles

Crystal structure prediction is an important first step on the path toward computational materials design. Increasingly robust methods have become available in recent years for computing many materials properties, but because properties are largely a function of crystal structure, the structure must be known before these methods can be brought to bear. In addition, structure prediction is particularly useful for identifying low-energy structures of subperiodic materials, such as two-dimensional (2D) materials, which may adopt unexpected structures that differ from those of the corresponding bulk phases. Evolutionary algorithms, which are heuristics for global optimization inspired by biological evolution, have proven to be a fruitful approach for tackling the problem of crystal structure prediction. This thesis describes the development of an improved evolutionary algorithm for structure prediction and several applications of the algorithm to predict the structures of novel low-energy 2D materials. The first part of this thesis contains an overview of evolutionary algorithms for crystal structure prediction and presents our implementation, including details of extending the algorithm to search for clusters, wires, and 2D materials, improvements to efficiency when running in parallel, improved composition space sampling, and the ability to search for partial phase diagrams. We then present several applications of the evolutionary algorithm to 2D systems, including InP, the C-Si and Sn-S phase diagrams, and several group-IV dioxides. This thesis makes use of the Cornell graduate school's "papers" option. Chapters 1 and 3 correspond to the first-author publications of Refs. [131] and [132], respectively, and chapter 2 will soon be submitted as a first-author publication. The material in chapter 4 is taken from Ref. [144], in which I share joint first-authorship. In this case I have included only my own contributions.

The Ordered Network Structure and Prediction Summary for M≥7 Earthquakes in Xinjiang Region of China

NASA Astrophysics Data System (ADS)

Men, Ke-Pei; Zhao, Kai

2014-12-01

M ≥7 earthquakes have showed an obvious commensurability and orderliness in Xinjiang of China and its adjacent region since 1800. The main orderly values are 30 a × k (k = 1,2,3), 11 12 a, 41 43 a, 18 19 a, and 5 6 a. In the guidance of the information forecasting theory of Wen-Bo Weng, based on previous research results, combining ordered network structure analysis with complex network technology, we focus on the prediction summary of M ≥ 7 earthquakes by using the ordered network structure, and add new information to further optimize network, hence construct the 2D- and 3D-ordered network structure of M ≥ 7 earthquakes. In this paper, the network structure revealed fully the regularity of seismic activity of M ≥ 7 earthquakes in the study region during the past 210 years. Based on this, the Karakorum M7.1 earthquake in 1996, the M7.9 earthquake on the frontier of Russia, Mongol, and China in 2003, and two Yutian M7.3 earthquakes in 2008 and 2014 were predicted successfully. At the same time, a new prediction opinion is presented that the future two M ≥ 7 earthquakes will probably occur around 2019 - 2020 and 2025 - 2026 in this region. The results show that large earthquake occurred in defined region can be predicted. The method of ordered network structure analysis produces satisfactory results for the mid-and-long term prediction of M ≥ 7 earthquakes.

Fast Geometric Consensus Approach for Protein Model Quality Assessment

PubMed Central

Adamczak, Rafal; Pillardy, Jaroslaw; Vallat, Brinda K.

2011-01-01

Abstract Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well. PMID:21244273

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

PubMed

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

NASA Astrophysics Data System (ADS)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Prediction and characterization of an Mg-Al intermetallic compound with potentially improved ductility via orbital-free and Kohn-Sham density functional theory

NASA Astrophysics Data System (ADS)

Zhuang, Houlong L.; Chen, Mohan; Carter, Emily A.

2017-10-01

Magnesium-aluminum (Mg-Al) intermetallic compounds that form as precipitates can significantly influence the mechanical properties of Mg-Al alloys. A computational evaluation of known and unknown Mg-Al intermetallic compounds could help design new Mg-Al alloy microstructures with optimal properties. Here, we employ the cluster-expansion method with energies efficiently calculated with orbital-free density functional theory (OFDFT) and predict a new, metastable intermetallic compound Mg3Al with a D019 hexagonal structure that is slightly more stable than an alternative L12 cubic structure. We apply Kohn-Sham DFT (KSDFT) to accurately evaluate various metastability criteria for D019 and L12 Mg3Al, including Born’s criterion and phonon dispersion. We show that both Mg3Al crystalline phases satisfy the metastability criteria and hence should be at least metastable. We further compare ductility metrics for D019 and L12 Mg3Al to that of hexagonal-close-packed Mg by computing Pugh’s ratio and generalized stacking fault energies. The ductility is predicted to follow the order: D019 Mg3Al > L12 Mg3Al > Mg, based on the highest Pugh’s ratio and the lowest unstable stacking and twinning fault energies of D019 Mg3Al compared to that of Mg. We also predict a very low antiphase boundary energy for Mg3Al and therefore expect D019 Mg3Al to be beneficial for improving the ductility of Mg-rich Mg-Al alloys. A computational design of Mg-Al alloy microstructures may become possible by combining the strengths of both OFDFT and KSDFT, i.e., the efficiency of the former and the accuracy of the latter, as demonstrated here.

The Sensitivity of Glacial Isostatic Adjustment in West Antarctica to Lateral Variations in Earth Structure

NASA Astrophysics Data System (ADS)

Nield, G.; Whitehouse, P. L.; Blank, B.; van der Wal, W.; O'Donnell, J. P.; Stuart, G. W.; Lloyd, A. J.; Wiens, D.

2017-12-01

Accurate models of Glacial Isostatic Adjustment (GIA) are required for correcting satellite measurements of ice-mass change and for interpretation of geodetic data at the location of present and former ice sheets. Global models of GIA tend to adopt a 1-D representation of Earth structure, varying in the radial direction only. In some regions rheological parameters may differ significantly from this global average leading to bias in model predictions of present-day deformation, geoid change rates and sea-level change. The advancement of 3-D GIA modelling techniques in recent years has led to improvements in the representation of the Earth via the incorporation of laterally varying structure. This study investigates the influence of 3-D Earth structure on deformation rates in West Antarctica using a finite element GIA model with power-law rheology. We utilise datasets of seismic velocity and temperature for the crust and upper mantle with the aim of determining a data-driven Earth model, and consider the differences when compared to deformation predicted from an equivalent 1-D Earth structure.

Integrating protein structural dynamics and evolutionary analysis with Bio3D.

PubMed

Skjærven, Lars; Yao, Xin-Qiu; Scarabelli, Guido; Grant, Barry J

2014-12-10

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

Engineering 3D Models of Tumors and Bone to Understand Tumor-Induced Bone Disease and Improve Treatments

PubMed Central

Kwakwa, Kristin A.; Vanderburgh, Joseph P.; Guelcher, Scott A.

2018-01-01

Purpose of Review Bone is a structurally unique microenvironment that presents many challenges for the development of 3D models for studying bone physiology and diseases, including cancer. As researchers continue to investigate the interactions within the bone microenvironment, the development of 3D models of bone has become critical. Recent Findings 3D models have been developed that replicate some properties of bone, but have not fully reproduced the complex structural and cellular composition of the bone microenvironment. This review will discuss 3D models including polyurethane, silk, and collagen scaffolds that have been developed to study tumor-induced bone disease. In addition, we discuss 3D printing techniques used to better replicate the structure of bone. Summary 3D models that better replicate the bone microenvironment will help researchers better understand the dynamic interactions between tumors and the bone microenvironment, ultimately leading to better models for testing therapeutics and predicting patient outcomes. PMID:28646444

Template CoMFA Generates Single 3D-QSAR Models that, for Twelve of Twelve Biological Targets, Predict All ChEMBL-Tabulated Affinities

PubMed Central

Cramer, Richard D.

2015-01-01

The possible applicability of the new template CoMFA methodology to the prediction of unknown biological affinities was explored. For twelve selected targets, all ChEMBL binding affinities were used as training and/or prediction sets, making these 3D-QSAR models the most structurally diverse and among the largest ever. For six of the targets, X-ray crystallographic structures provided the aligned templates required as input (BACE, cdk1, chk2, carbonic anhydrase-II, factor Xa, PTP1B). For all targets including the other six (hERG, cyp3A4 binding, endocrine receptor, COX2, D2, and GABAa), six modeling protocols applied to only three familiar ligands provided six alternate sets of aligned templates. The statistical qualities of the six or seven models thus resulting for each individual target were remarkably similar. Also, perhaps unexpectedly, the standard deviations of the errors of cross-validation predictions accompanying model derivations were indistinguishable from the standard deviations of the errors of truly prospective predictions. These standard deviations of prediction ranged from 0.70 to 1.14 log units and averaged 0.89 (8x in concentration units) over the twelve targets, representing an average reduction of almost 50% in uncertainty, compared to the null hypothesis of “predicting” an unknown affinity to be the average of known affinities. These errors of prediction are similar to those from Tanimoto coefficients of fragment occurrence frequencies, the predominant approach to side effect prediction, which template CoMFA can augment by identifying additional active structural classes, by improving Tanimoto-only predictions, by yielding quantitative predictions of potency, and by providing interpretable guidance for avoiding or enhancing any specific target response. PMID:26065424

Lessons learned from participating in D3R 2016 Grand Challenge 2: compounds targeting the farnesoid X receptor

NASA Astrophysics Data System (ADS)

Duan, Rui; Xu, Xianjin; Zou, Xiaoqin

2018-01-01

D3R 2016 Grand Challenge 2 focused on predictions of binding modes and affinities for 102 compounds against the farnesoid X receptor (FXR). In this challenge, two distinct methods, a docking-based method and a template-based method, were employed by our team for the binding mode prediction. For the new template-based method, 3D ligand similarities were calculated for each query compound against the ligands in the co-crystal structures of FXR available in Protein Data Bank. The binding mode was predicted based on the co-crystal protein structure containing the ligand with the best ligand similarity score against the query compound. For the FXR dataset, the template-based method achieved a better performance than the docking-based method on the binding mode prediction. For the binding affinity prediction, an in-house knowledge-based scoring function ITScore2 and MM/PBSA approach were employed. Good performance was achieved for MM/PBSA, whereas the performance of ITScore2 was sensitive to ligand composition, e.g. the percentage of carbon atoms in the compounds. The sensitivity to ligand composition could be a clue for the further improvement of our knowledge-based scoring function.

Resource for structure related information on transmembrane proteins

NASA Astrophysics Data System (ADS)

Tusnády, Gábor E.; Simon, István

Transmembrane proteins are involved in a wide variety of vital biological processes including transport of water-soluble molecules, flow of information and energy production. Despite significant efforts to determine the structures of these proteins, only a few thousand solved structures are known so far. Here, we review the various resources for structure-related information on these types of proteins ranging from the 3D structure to the topology and from the up-to-date databases to the various Internet sites and servers dealing with structure prediction and structure analysis. Abbreviations: 3D, three dimensional; PDB, Protein Data Bank; TMP, transmembrane protein.

Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives.

PubMed

Gao, Jia-Suo; Tong, Xu-Peng; Chang, Yi-Qun; He, Yu-Xuan; Mei, Yu-Dan; Tan, Pei-Hong; Guo, Jia-Liang; Liao, Guo-Chao; Xiao, Gao-Keng; Chen, Wei-Min; Zhou, Shu-Feng; Sun, Ping-Hua

2015-01-01

Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q (2) values of 0.753 and 0.770, and r (2) values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2'-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure-property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature.

Screening Libraries of Semifluorinated Arylene Bisimides to Discover and Predict Thermodynamically Controlled Helical Crystallization.

PubMed

Ho, Ming-Shou; Partridge, Benjamin E; Sun, Hao-Jan; Sahoo, Dipankar; Leowanawat, Pawaret; Peterca, Mihai; Graf, Robert; Spiess, Hans W; Zeng, Xiangbing; Ungar, Goran; Heiney, Paul A; Hsu, Chain-Shu; Percec, Virgil

2016-12-12

Synthesis, structural, and retrostructural analysis of a library containing 16 self-assembling perylene (PBI), 1,6,7,12-tetrachloroperylene (Cl 4 PBI), naphthalene (NBI), and pyromellitic (PMBI) bisimides functionalized with environmentally friendly AB 3 chiral racemic semifluorinated minidendrons at their imide groups via m = 0, 1, 2, and 3 methylene units is reported. These semifluorinated compounds melt at lower temperatures than homologous hydrogenated compounds, permitting screening of all their thermotropic phases via structural analysis to discover thermodynamically controlled helical crystallization from propeller-like, cogwheel, and tilted molecules as well as lamellar-like structures. Thermodynamically controlled helical crystallization was discovered for propeller-like PBI, Cl 4 PBI and NBI with m = 0. Unexpectedly, assemblies of twisted Cl 4 PBIs exhibit higher order than those of planar PBIs. PBI with m = 1, 2, and 3 form a thermodynamically controlled columnar hexagonal 2D lattice of tilted helical columns with intracolumnar order. PBI and Cl 4 PBI with m = 1 crystallize via a recently discovered helical cogwheel mechanism, while NBI and PMBI with m = 1 form tilted helical columns. PBI, NBI and PMBI with m = 2 generate lamellar-like structures. 3D and 2D assemblies of PBI with m = 1, 2, and 3, NBI with m = 1 and PMBI with m = 2 exhibit 3.4 Å π-π stacking. The library approach applied here and in previous work enabled the discovery of six assemblies which self-organize via thermodynamic control into 3D and 2D periodic arrays, and provides molecular principles to predict the supramolecular structure of electronically active components.

Predicting the structural and electronic properties of two-dimensional single layer boron nitride sheets

NASA Astrophysics Data System (ADS)

Li, Xiao-Dong; Cheng, Xin-Lu

2018-02-01

Three two-dimensional (2D) single layer boron nitride sheets have been predicted based on the first-principles calculations. These 2D boron nitride sheets are comprised of equivalent boron atoms and nitride atoms with sp2 and sp bond hybridization. The geometry optimization reflects that they all possess stable planar crystal structures with the space group P 6 bar 2 m (D3h3) symmetry. The charge density distribution manifests that the B-N bonds in these boron nitride sheets are covalent in nature but with ionic characteristics. The tunable band gaps indicate their potential applications in nanoscale electronic and optoelectronic devices by changing the length of sp-bonded Bsbnd N linkages.

Automated and fast building of three-dimensional RNA structures.

PubMed

Zhao, Yunjie; Huang, Yangyu; Gong, Zhou; Wang, Yanjie; Man, Jianfen; Xiao, Yi

2012-01-01

Building tertiary structures of non-coding RNA is required to understand their functions and design new molecules. Current algorithms of RNA tertiary structure prediction give satisfactory accuracy only for small size and simple topology and many of them need manual manipulation. Here, we present an automated and fast program, 3dRNA, for RNA tertiary structure prediction with reasonable accuracy for RNAs of larger size and complex topology.

Computational analysis of histidine mutations on the structural stability of human tyrosinases leading to albinism insurgence.

PubMed

Hassan, Mubashir; Abbas, Qamar; Raza, Hussain; Moustafa, Ahmed A; Seo, Sung-Yum

2017-07-25

Misfolding and structural alteration in proteins lead to serious malfunctions and cause various diseases in humans. Mutations at the active binding site in tyrosinase impair structural stability and cause lethal albinism by abolishing copper binding. To evaluate the histidine mutational effect, all mutated structures were built using homology modelling. The protein sequence was retrieved from the UniProt database, and 3D models of original and mutated human tyrosinase sequences were predicted by changing the residual positions within the target sequence separately. Structural and mutational analyses were performed to interpret the significance of mutated residues (N 180 , R 202 , Q 202 , R 211 , Y 363 , R 367 , Y 367 and D 390 ) at the active binding site of tyrosinases. CSpritz analysis depicted that 23.25% residues actively participate in the instability of tyrosinase. The accuracy of predicted models was confirmed through online servers ProSA-web, ERRAT score and VERIFY 3D values. The theoretical pI and GRAVY generated results also showed the accuracy of the predicted models. The CCA negative correlation results depicted that the replacement of mutated residues at His within the active binding site disturbs the structural stability of tyrosinases. The predicted CCA scores of Tyr 367 (-0.079) and Q/R 202 (0.032) revealed that both mutations have more potential to disturb the structural stability. MD simulation analyses of all predicted models justified that Gln 202 , Arg 202 , Tyr 367 and D 390 replacement made the protein structures more susceptible to destabilization. Mutational results showed that the replacement of His with Q/R 202 and Y/R 363 has a lethal effect and may cause melanin associated diseases such as OCA1. Taken together, our computational analysis depicts that the mutated residues such as Q/R 202 and Y/R 363 actively participate in instability and misfolding of tyrosinases, which may govern OCA1 through disturbing the melanin biosynthetic pathway.

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

NASA Astrophysics Data System (ADS)

Mey, Antonia S. J. S.; Jiménez, Jordi Juárez; Michel, Julien

2018-01-01

The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.

Structured Light-Based 3D Reconstruction System for Plants

PubMed Central

Nguyen, Thuy Tuong; Slaughter, David C.; Max, Nelson; Maloof, Julin N.; Sinha, Neelima

2015-01-01

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants.This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance. PMID:26230701

Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis.

PubMed

Ivorra, Eugenio; Verdu, Samuel; Sánchez, Antonio J; Grau, Raúl; Barat, José M

2016-10-19

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0-6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead's pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R² of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness.

Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis

PubMed Central

Ivorra, Eugenio; Verdu, Samuel; Sánchez, Antonio J.; Grau, Raúl; Barat, José M.

2016-01-01

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0–6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead’s pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R2 of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness. PMID:27775556

Development of a 3D finite element acoustic model to predict the sound reduction index of stud based double-leaf walls

NASA Astrophysics Data System (ADS)

Arjunan, A.; Wang, C. J.; Yahiaoui, K.; Mynors, D. J.; Morgan, T.; Nguyen, V. B.; English, M.

2014-11-01

Building standards incorporating quantitative acoustical criteria to ensure adequate sound insulation are now being implemented. Engineers are making great efforts to design acoustically efficient double-wall structures. Accordingly, efficient simulation models to predict the acoustic insulation of double-leaf wall structures are needed. This paper presents the development of a numerical tool that can predict the frequency dependent sound reduction index R of stud based double-leaf walls at one-third-octave band frequency range. A fully vibro-acoustic 3D model consisting of two rooms partitioned using a double-leaf wall, considering the structure and acoustic fluid coupling incorporating the existing fluid and structural solvers are presented. The validity of the finite element (FE) model is assessed by comparison with experimental test results carried out in a certified laboratory. Accurate representation of the structural damping matrix to effectively predict the R values are studied. The possibilities of minimising the simulation time using a frequency dependent mesh model was also investigated. The FEA model presented in this work is capable of predicting the weighted sound reduction index Rw along with A-weighted pink noise C and A-weighted urban noise Ctr within an error of 1 dB. The model developed can also be used to analyse the acoustically induced frequency dependent geometrical behaviour of the double-leaf wall components to optimise them for best acoustic performance. The FE modelling procedure reported in this paper can be extended to other building components undergoing fluid-structure interaction (FSI) to evaluate their acoustic insulation.

Structure, stability, thermodynamic properties, and IR spectra of the protonated water decamer H+(H2O)10.

PubMed

Karthikeyan, S; Kim, Kwang S

2009-08-13

Protonated water clusters H+(H2O)n favor two-dimensional (2D) structures for n < or = 7 at low temperatures. At 0 K, the 2D and three-dimensional (3D) structures for n = 8 are almost isoenergetic, and the 3D structures for n > 9 tend to be more stable. However, for n = 9, the netlike structures are likely to be more stable above 150 K. In this regard, we investigate the case of n = 10 to find which structure is more stable between the 3D structure and the netlike structure around 150 and 250 K. We use density functional theory, Møller-Plesset second-order perturbation theory, and coupled cluster theory with single, double, and perturbative triple excitations (CCSD(T)). At the complete basis set limit for the CCSD(T) level of theory, three isomers of 3D cage structure are much more stable in zero point energy corrected binding energy and in free binding energies at 150 K than the lowest energy netlike structures, while the netlike structure would be more stable around approximately 250 K. The predicted vibrational spectra are in good agreement with the experiment. One of the three isomers explains the experimental IR observation of an acceptor (A) type peak of a dangling hydrogen atom.

MISS-Prot: web server for self/non-self discrimination of protein residue networks in parasites; theory and experiments in Fasciola peptides and Anisakis allergens.

PubMed

González-Díaz, Humberto; Muíño, Laura; Anadón, Ana M; Romaris, Fernanda; Prado-Prado, Francisco J; Munteanu, Cristian R; Dorado, Julián; Sierra, Alejandro Pazos; Mezo, Mercedes; González-Warleta, Marta; Gárate, Teresa; Ubeira, Florencio M

2011-06-01

Infections caused by human parasites (HPs) affect the poorest 500 million people worldwide but chemotherapy has become expensive, toxic, and/or less effective due to drug resistance. On the other hand, many 3D structures in Protein Data Bank (PDB) remain without function annotation. We need theoretical models to quickly predict biologically relevant Parasite Self Proteins (PSP), which are expressed differentially in a given parasite and are dissimilar to proteins expressed in other parasites and have a high probability to become new vaccines (unique sequence) or drug targets (unique 3D structure). We present herein a model for PSPs in eight different HPs (Ascaris, Entamoeba, Fasciola, Giardia, Leishmania, Plasmodium, Trypanosoma, and Toxoplasma) with 90% accuracy for 15 341 training and validation cases. The model combines protein residue networks, Markov Chain Models (MCM) and Artificial Neural Networks (ANN). The input parameters are the spectral moments of the Markov transition matrix for electrostatic interactions associated with the protein residue complex network calculated with the MARCH-INSIDE software. We implemented this model in a new web-server called MISS-Prot (MARCH-INSIDE Scores for Self-Proteins). MISS-Prot was programmed using PHP/HTML/Python and MARCH-INSIDE routines and is freely available at: . This server is easy to use by non-experts in Bioinformatics who can carry out automatic online upload and prediction with 3D structures deposited at PDB (mode 1). We can also study outcomes of Peptide Mass Fingerprinting (PMFs) and MS/MS for query proteins with unknown 3D structures (mode 2). We illustrated the use of MISS-Prot in experimental and/or theoretical studies of peptides from Fasciola hepatica cathepsin proteases or present on 10 Anisakis simplex allergens (Ani s 1 to Ani s 10). In doing so, we combined electrophoresis (1DE), MALDI-TOF Mass Spectroscopy, and MASCOT to seek sequences, Molecular Mechanics + Molecular Dynamics (MM/MD) to generate 3D structures and MISS-Prot to predict PSP scores. MISS-Prot also allows the prediction of PSP proteins in 16 additional species including parasite hosts, fungi pathogens, disease transmission vectors, and biotechnologically relevant organisms.

Protein structure database search and evolutionary classification.

PubMed

Yang, Jinn-Moon; Tung, Chi-Hua

2006-01-01

As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].

Predicting vapor liquid equilibria using density functional theory: A case study of argon

NASA Astrophysics Data System (ADS)

Goel, Himanshu; Ling, Sanliang; Ellis, Breanna Nicole; Taconi, Anna; Slater, Ben; Rai, Neeraj

2018-06-01

Predicting vapor liquid equilibria (VLE) of molecules governed by weak van der Waals (vdW) interactions using the first principles approach is a significant challenge. Due to the poor scaling of the post Hartree-Fock wave function theory with system size/basis functions, the Kohn-Sham density functional theory (DFT) is preferred for systems with a large number of molecules. However, traditional DFT cannot adequately account for medium to long range correlations which are necessary for modeling vdW interactions. Recent developments in DFT such as dispersion corrected models and nonlocal van der Waals functionals have attempted to address this weakness with a varying degree of success. In this work, we predict the VLE of argon and assess the performance of several density functionals and the second order Møller-Plesset perturbation theory (MP2) by determining critical and structural properties via first principles Monte Carlo simulations. PBE-D3, BLYP-D3, and rVV10 functionals were used to compute vapor liquid coexistence curves, while PBE0-D3, M06-2X-D3, and MP2 were used for computing liquid density at a single state point. The performance of the PBE-D3 functional for VLE is superior to other functionals (BLYP-D3 and rVV10). At T = 85 K and P = 1 bar, MP2 performs well for the density and structural features of the first solvation shell in the liquid phase.

The Proteome Folding Project: Proteome-scale prediction of structure and function

PubMed Central

Drew, Kevin; Winters, Patrick; Butterfoss, Glenn L.; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David R.; Davis, Trisha N.; Shasha, Dennis; Malmström, Lars; Bonneau, Richard

2011-01-01

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions. PMID:21824995

Structural mechanics of 3-D braided preforms for composites. IV - The 4-step tubular braiding

NASA Technical Reports Server (NTRS)

Hammad, M.; El-Messery, M.; El-Shiekh, A.

1991-01-01

This paper presents the fundamentals of the 4-step 3D tubular braiding process and the structure of the preforms produced. Based on an idealized structural model, geometric relations between the structural parameters of the preform are analytically established. The effects of machine arrangement and operating conditions are discussed. Yarn retraction, yarn surface angle, outside diameter, and yarn volume fraction of the preform in terms of the pitch length, the inner diameter, and the machine arrangement are theoretically predicted and experimentally verified.

Quantitative power Doppler ultrasound measures of peripheral joint synovitis in poor prognosis early rheumatoid arthritis predict radiographic progression.

PubMed

Sreerangaiah, Dee; Grayer, Michael; Fisher, Benjamin A; Ho, Meilien; Abraham, Sonya; Taylor, Peter C

2016-01-01

To assess the value of quantitative vascular imaging by power Doppler US (PDUS) as a tool that can be used to stratify patient risk of joint damage in early seropositive RA while still biologic naive but on synthetic DMARD treatment. Eighty-five patients with seropositive RA of <3 years duration had clinical, laboratory and imaging assessments at 0 and 12 months. Imaging assessments consisted of radiographs of the hands and feet, two-dimensional (2D) high-frequency and PDUS imaging of 10 MCP joints that were scored for erosions and vascularity and three-dimensional (3D) PDUS of MCP joints and wrists that were scored for vascularity. Severe deterioration on radiographs and ultrasonography was seen in 45 and 28% of patients, respectively. The 3D power Doppler volume and 2D vascularity scores were the most useful US predictors of deterioration. These variables were modelled in two equations that estimate structural damage over 12 months. The equations had a sensitivity of 63.2% and specificity of 80.9% for predicting radiographic structural damage and a sensitivity of 54.2% and specificity of 96.7% for predicting structural damage on ultrasonography. In seropositive early RA, quantitative vascular imaging by PDUS has clinical utility in predicting which patients will derive benefit from early use of biologic therapy. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Optimal contact definition for reconstruction of contact maps.

PubMed

Duarte, Jose M; Sathyapriya, Rajagopal; Stehr, Henning; Filippis, Ioannis; Lappe, Michael

2010-05-27

Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction. However a contact map's biological interest is subject to the availability of reliable methods for the 3-dimensional reconstruction of the structure. We use an implementation of the well-known distance geometry protocol to build realistic protein 3-dimensional models from contact maps, performing an extensive exploration of many of the parameters involved in the reconstruction process. We try to address the questions: a) to what accuracy does a contact map represent its corresponding 3D structure, b) what is the best contact map representation with regard to reconstructability and c) what is the effect of partial or inaccurate contact information on the 3D structure recovery. Our results suggest that contact maps derived from the application of a distance cutoff of 9 to 11A around the Cbeta atoms constitute the most accurate representation of the 3D structure. The reconstruction process does not provide a single solution to the problem but rather an ensemble of conformations that are within 2A RMSD of the crystal structure and with lower values for the pairwise average ensemble RMSD. Interestingly it is still possible to recover a structure with partial contact information, although wrong contacts can lead to dramatic loss in reconstruction fidelity. Thus contact maps represent a valid approximation to the structures with an accuracy comparable to that of experimental methods. The optimal contact definitions constitute key guidelines for methods based on contact maps such as structure prediction through contacts and structural alignments based on maximum contact map overlap.

Optimal contact definition for reconstruction of Contact Maps

PubMed Central

2010-01-01

Background Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction. However a contact map's biological interest is subject to the availability of reliable methods for the 3-dimensional reconstruction of the structure. Results We use an implementation of the well-known distance geometry protocol to build realistic protein 3-dimensional models from contact maps, performing an extensive exploration of many of the parameters involved in the reconstruction process. We try to address the questions: a) to what accuracy does a contact map represent its corresponding 3D structure, b) what is the best contact map representation with regard to reconstructability and c) what is the effect of partial or inaccurate contact information on the 3D structure recovery. Our results suggest that contact maps derived from the application of a distance cutoff of 9 to 11Å around the Cβ atoms constitute the most accurate representation of the 3D structure. The reconstruction process does not provide a single solution to the problem but rather an ensemble of conformations that are within 2Å RMSD of the crystal structure and with lower values for the pairwise average ensemble RMSD. Interestingly it is still possible to recover a structure with partial contact information, although wrong contacts can lead to dramatic loss in reconstruction fidelity. Conclusions Thus contact maps represent a valid approximation to the structures with an accuracy comparable to that of experimental methods. The optimal contact definitions constitute key guidelines for methods based on contact maps such as structure prediction through contacts and structural alignments based on maximum contact map overlap. PMID:20507547

Modularization and Validation of FUN3D as a CREATE-AV Helios Near-Body Solver

NASA Technical Reports Server (NTRS)

Jain, Rohit; Biedron, Robert T.; Jones, William T.; Lee-Rausch, Elizabeth M.

2016-01-01

Under a recent collaborative effort between the US Army Aeroflightdynamics Directorate (AFDD) and NASA Langley, NASA's general unstructured CFD solver, FUN3D, was modularized as a CREATE-AV Helios near-body unstructured grid solver. The strategies adopted in Helios/FUN3D integration effort are described. A validation study of the new capability is performed for rotorcraft cases spanning hover prediction, airloads prediction, coupling with computational structural dynamics, counter-rotating dual-rotor configurations, and free-flight trim. The integration of FUN3D, along with the previously integrated NASA OVERFLOW solver, lays the ground for future interaction opportunities where capabilities of one component could be leveraged with those of others in a relatively seamless fashion within CREATE-AV Helios.

Characterization of 3d Contact Kinematics and Prediction of Resonant Response of Structures Having 3d Frictional Constraint

NASA Astrophysics Data System (ADS)

Yang, B. D.; Menq, C. H.

1998-11-01

A 3D friction contact model has been developed for the prediction of the resonant response of structures having 3D frictional constraint. In the proposed model, a contact plane is defined and its orientation is assumed invariant. Consequently, the relative motion of the two contacting surfaces can be resolved into two components: the in-plane tangential motion on the contact plane and the normal component perpendicular to the plane. The in-plane tangential relative motion is often two-dimensional, and it can induce stick-slip friction. On the other hand, the normal relative motion can cause variation of the contact normal load and, in extreme circumstances, separation of the two contacting surfaces. In this study, the joined effect of the 2D tangential relative motion and the normal relative motion on the contact kinematics of a friction contact is examined and analytical criteria are developed to determine the transitions among stick, slip, and separation, when experiencing variable normal load. With these transition criteria, the induced friction force on the contact plane and the variable normal load perpendicular to the plane can be predicted for any given cyclic relative motions at the contact interface and hysteresis loops can be produced so as to characterize the equivalent damping and stiffness of the friction contact. These non-linear damping and stiffness along with the harmonic balance method are then used to predict the resonance of a frictionally constrained 3-DOF oscillator. The predicted results are compared with those of the time integration method and the damping effect, the resonant frequency shift, and the jump phenomenon are examined.

Simulation of unsteady state performance of a secondary air system by the 1D-3D-Structure coupled method

NASA Astrophysics Data System (ADS)

Wu, Hong; Li, Peng; Li, Yulong

2016-02-01

This paper describes the calculation method for unsteady state conditions in the secondary air systems in gas turbines. The 1D-3D-Structure coupled method was applied. A 1D code was used to model the standard components that have typical geometric characteristics. Their flow and heat transfer were described by empirical correlations based on experimental data or CFD calculations. A 3D code was used to model the non-standard components that cannot be described by typical geometric languages, while a finite element analysis was carried out to compute the structural deformation and heat conduction at certain important positions. These codes were coupled through their interfaces. Thus, the changes in heat transfer and structure and their interactions caused by exterior disturbances can be reflected. The results of the coupling method in an unsteady state showed an apparent deviation from the existing data, while the results in the steady state were highly consistent with the existing data. The difference in the results in the unsteady state was caused primarily by structural deformation that cannot be predicted by the 1D method. Thus, in order to obtain the unsteady state performance of a secondary air system more accurately and efficiently, the 1D-3D-Structure coupled method should be used.

Reliable resonance assignments of selected residues of proteins with known structure based on empirical NMR chemical shift prediction

NASA Astrophysics Data System (ADS)

Li, Da-Wei; Meng, Dan; Brüschweiler, Rafael

2015-05-01

A robust NMR resonance assignment method is introduced for proteins whose 3D structure has previously been determined by X-ray crystallography. The goal of the method is to obtain a subset of correct assignments from a parsimonious set of 3D NMR experiments of 15N, 13C labeled proteins. Chemical shifts of sequential residue pairs are predicted from static protein structures using PPM_One, which are then compared with the corresponding experimental shifts. Globally optimized weighted matching identifies the assignments that are robust with respect to small changes in NMR cross-peak positions. The method, termed PASSPORT, is demonstrated for 4 proteins with 100-250 amino acids using 3D NHCA and a 3D CBCA(CO)NH experiments as input producing correct assignments with high reliability for 22% of the residues. The method, which works best for Gly, Ala, Ser, and Thr residues, provides assignments that serve as anchor points for additional assignments by both manual and semi-automated methods or they can be directly used for further studies, e.g. on ligand binding, protein dynamics, or post-translational modification, such as phosphorylation.

Reliable Resonance Assignments of Selected Residues of Proteins with Known Structure Based on Empirical NMR Chemical Shift Prediction

PubMed Central

Li, Da-Wei; Meng, Dan; Brüschweiler, Rafael

2015-01-01

A robust NMR resonance assignment method is introduced for proteins whose 3D structure has previously been determined by X-ray crystallography. The goal of the method is to obtain a subset of correct assignments from a parsimonious set of 3D NMR experiments of 15N, 13C labeled proteins. Chemical shifts of sequential residue pairs are predicted from static protein structures using PPM_One, which are then compared with the corresponding experimental shifts. Globally optimized weighted matching identifies the assignments that are robust with respect to small changes in NMR cross-peak positions. The method, termed PASSPORT, is demonstrated for 4 proteins with 100 – 250 amino acids using 3D NHCA and a 3D CBCA(CO)NH experiments as input producing correct assignments with high reliability for 22% of the residues. The method, which works best for Gly, Ala, Ser, and Thr residues, provides assignments that serve as anchor points for additional assignments by both manual and semi-automated methods or they can be directly used for further studies, e.g. on ligand binding, protein dynamics, or post-translational modification, such as phosphorylation. PMID:25863893

3D-QSAR studies on the inhibitory activity of trimethoprim analogues against Escherichia coli dihydrofolate reductase.

PubMed

Vijayaraj, Ramadoss; Devi, Mekapothula Lakshmi Vasavi; Subramanian, Venkatesan; Chattaraj, Pratim Kumar

2012-06-01

Three-dimensional quantitative structure activity relationship (3D-QSAR) study has been carried out on the Escherichia coli DHFR inhibitors 2,4-diamino-5-(substituted-benzyl)pyrimidine derivatives to understand the structural features responsible for the improved potency. To construct highly predictive 3D-QSAR models, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were used. The predicted models show statistically significant cross-validated and non-cross-validated correlation coefficient of r2 CV and r2 nCV, respectively. The final 3D-QSAR models were validated using structurally diverse test set compounds. Analysis of the contour maps generated from CoMFA and CoMSIA methods reveals that the substitution of electronegative groups at the first and second position along with electropositive group at the third position of R2 substitution significantly increases the potency of the derivatives. The results obtained from the CoMFA and CoMSIA study delineate the substituents on the trimethoprim analogues responsible for the enhanced potency and also provide valuable directions for the design of new trimethoprim analogues with improved affinity. © 2012 John Wiley & Sons A/S.

Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas

PubMed Central

Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.

2013-01-01

The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545

Comprehending 3D Diagrams: Sketching to Support Spatial Reasoning.

PubMed

Gagnier, Kristin M; Atit, Kinnari; Ormand, Carol J; Shipley, Thomas F

2017-10-01

Science, technology, engineering, and mathematics (STEM) disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants' comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D slice through 3D geologic block diagrams. Generating sketches that predicated the internal structure of a model led to greater improvement in diagram understanding than visualizing the interior of the model without sketching, or sketching the model without attempting to predict unseen spatial relations. In addition, we found a positive correlation between sketched diagram accuracy and improvement on the diagram comprehension measure. Results suggest that generating a predictive diagram facilitates students' abilities to make inferences about spatial relationships in diagrams. Implications for use of sketching in supporting STEM learning are discussed. Copyright © 2016 Cognitive Science Society, Inc.

GARN: Sampling RNA 3D Structure Space with Game Theory and Knowledge-Based Scoring Strategies.

PubMed

Boudard, Mélanie; Bernauer, Julie; Barth, Dominique; Cohen, Johanne; Denise, Alain

2015-01-01

Cellular processes involve large numbers of RNA molecules. The functions of these RNA molecules and their binding to molecular machines are highly dependent on their 3D structures. One of the key challenges in RNA structure prediction and modeling is predicting the spatial arrangement of the various structural elements of RNA. As RNA folding is generally hierarchical, methods involving coarse-grained models hold great promise for this purpose. We present here a novel coarse-grained method for sampling, based on game theory and knowledge-based potentials. This strategy, GARN (Game Algorithm for RNa sampling), is often much faster than previously described techniques and generates large sets of solutions closely resembling the native structure. GARN is thus a suitable starting point for the molecular modeling of large RNAs, particularly those with experimental constraints. GARN is available from: http://garn.lri.fr/.

Bioinformatics approaches for structural and functional analysis of proteins in secondary metabolism in Withania somnifera.

PubMed

Sanchita; Singh, Swati; Sharma, Ashok

2014-11-01

Withania somnifera (Ashwagandha) is an affluent storehouse of large number of pharmacologically active secondary metabolites known as withanolides. These secondary metabolites are produced by withanolide biosynthetic pathway. Very less information is available on structural and functional aspects of enzymes involved in withanolides biosynthetic pathways of Withiana somnifera. We therefore performed a bioinformatics analysis to look at functional and structural properties of these important enzymes. The pathway enzymes taken for this study were 3-Hydroxy-3-methylglutaryl coenzyme A reductase, 1-Deoxy-D-xylulose-5-phosphate synthase, 1-Deoxy-D-xylulose-5-phosphate reductase, farnesyl pyrophosphate synthase, squalene synthase, squalene epoxidase, and cycloartenol synthase. The prediction of secondary structure was performed for basic structural information. Three-dimensional structures for these enzymes were predicted. The physico-chemical properties such as pI, AI, GRAVY and instability index were also studied. The current information will provide a platform to know the structural attributes responsible for the function of these protein until experimental structures become available.

Ultrathin thermoresponsive self-folding 3D graphene

PubMed Central

Xu, Weinan; Qin, Zhao; Chen, Chun-Teh; Kwag, Hye Rin; Ma, Qinli; Sarkar, Anjishnu; Buehler, Markus J.; Gracias, David H.

2017-01-01

Graphene and other two-dimensional materials have unique physical and chemical properties of broad relevance. It has been suggested that the transformation of these atomically planar materials to three-dimensional (3D) geometries by bending, wrinkling, or folding could significantly alter their properties and lead to novel structures and devices with compact form factors, but strategies to enable this shape change remain limited. We report a benign thermally responsive method to fold and unfold monolayer graphene into predesigned, ordered 3D structures. The methodology involves the surface functionalization of monolayer graphene using ultrathin noncovalently bonded mussel-inspired polydopamine and thermoresponsive poly(N-isopropylacrylamide) brushes. The functionalized graphene is micropatterned and self-folds into ordered 3D structures with reversible deformation under a full control by temperature. The structures are characterized using spectroscopy and microscopy, and self-folding is rationalized using a multiscale molecular dynamics model. Our work demonstrates the potential to design and fabricate ordered 3D graphene structures with predictable shape and dynamics. We highlight applicability by encapsulating live cells and creating nonlinear resistor and creased transistor devices. PMID:28989963

Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d.

PubMed

Doxey, Andrew C; Cheng, Zhenyu; Moffatt, Barbara A; McConkey, Brendan J

2010-08-03

Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB) for coplanar aromatic motifs similar to those found in known glycan-binding proteins. The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO) enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192) in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

High transport and excellent optical property of a two-dimensional single-layered hybrid perovskite (C4H9NH3)2PbBr4: a theoretical study.

PubMed

Lei, Jun-Hui; Zhao, Yu-Qing; Tang, Qiong; Lin, Jian-Guo; Cai, Meng-Qiu

2018-05-16

Organic-inorganic hybrid perovskites are developed to pursue high charge carrier mobility and light absorption coefficient. In this study, we present a detailed comparative research of the atomic and electronic structures of single-layered perovskites (C4H9NH3)2PbBr4 with two-dimensional/three-dimensional (2D/3D) spatial arrangement to predict the in plane charge carrier mobility along with the charge effective mass, elastic constant, and deformation potential. The calculated results reveal that the intrinsic in plane carrier mobilities of 2D single-layered hybrid perovskite (C4H9NH3)2PbBr4 along the 100 and 010 directions are superior to those of the 3D structure. Furthermore, the optical properties are calculated from the electronic structure; it is found that the light absorption spectrum of 2D single-layered perovskite (C4H9NH3)2PbBr4 with a high absorption coefficient is wider than that of the 3D phase. We speculate that the superior mobility and wider absorption spectrum of the 2D mono-layered perovskite are due to high charge density and ferroelectricity originating from structure distortion upon 3D-to-2D structure transformation. These results indicate that the 2D single-layered hybrid perovskite (C4H9NH3)2PbBr4 is a potential candidate for application in the optoelectronic and photovoltaic fields.

Unraveling the meaning of chemical shifts in protein NMR.

PubMed

Berjanskii, Mark V; Wishart, David S

2017-11-01

Chemical shifts are among the most informative parameters in protein NMR. They provide wealth of information about protein secondary and tertiary structure, protein flexibility, and protein-ligand binding. In this report, we review the progress in interpreting and utilizing protein chemical shifts that has occurred over the past 25years, with a particular focus on the large body of work arising from our group and other Canadian NMR laboratories. More specifically, this review focuses on describing, assessing, and providing some historical context for various chemical shift-based methods to: (1) determine protein secondary and super-secondary structure; (2) derive protein torsion angles; (3) assess protein flexibility; (4) predict residue accessible surface area; (5) refine 3D protein structures; (6) determine 3D protein structures and (7) characterize intrinsically disordered proteins. This review also briefly covers some of the methods that we previously developed to predict chemical shifts from 3D protein structures and/or protein sequence data. It is hoped that this review will help to increase awareness of the considerable utility of NMR chemical shifts in structural biology and facilitate more widespread adoption of chemical-shift based methods by the NMR spectroscopists, structural biologists, protein biophysicists, and biochemists worldwide. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigation of surface wave amplitudes in 3-D velocity and 3-D Q models

NASA Astrophysics Data System (ADS)

Ruan, Y.; Zhou, Y.

2010-12-01

It has been long recognized that seismic amplitudes depend on both wave speed structures and anelasticity (Q) structures. However, the effects of lateral heterogeneities in wave speed and Q structures on seismic amplitudes has not been well understood. We investigate the effects of 3-D wave speed and 3-D anelasticity (Q) structures on surface-wave amplitudes based upon wave propagation simulations of twelve globally-distributed earthquakes and 801 stations in Earth models with and without lateral heterogeneities in wave speed and anelasticity using a Spectral Element Method (SEM). Our tomographic-like 3-D Q models are converted from a velocity model S20RTS using a set of reasonable mineralogical parameters, assuming lateral perturbations in both velocity and Q are due to temperature perturbations. Surface-wave amplitude variations of SEM seismograms are measured in the period range of 50--200 s using boxcar taper, cosine taper and Slepian multi-tapers. We calculate ray-theoretical predictions of surface-wave amplitude perturbations due to elastic focusing, attenuation, and anelastic focusing which respectively depend upon the second spatial derivative (''roughness'') of perturbations in phase velocity, 1/Q, and the roughness of perturbations in 1/Q. Both numerical experiments and theoretical calculations show that (1) for short-period (~ 50 s) surface waves, the effects of amplitude attenuation due to 3-D Q structures are comparable with elastic focusing effects due to 3-D wave speed structures; and (2) for long-period (> 100 s) surface waves, the effects of attenuation become much weaker than elastic focusing; and (3) elastic focusing effects are correlated with anelastic focusing at all periods due to the correlation between velocity and Q models; and (4) amplitude perturbations are depend on measurement techniques and therefore cannot be directly compared with ray-theoretical predictions because ray theory does not account for the effects of measurement techniques. We calculate 3-D finite-frequency sensitivity of surface-wave amplitude to perturbations in wave speed and anelasticity (Q) which fully account for the effects of elastic focusing, attenuation, anelastic focusing as well as measurement techniques. We show that amplitude perturbations calculated using wave speed and Q sensitivity kernels agree reasonably well with SEM measurements and therefore the sensitivity kernels can be used in a joint inversion of seismic phase delays and amplitudes to simultaneously image high resolution 3-D wave speed and 3-D Q structures in the upper mantle.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

NASA Astrophysics Data System (ADS)

Costanzi, Stefano; Tikhonova, Irina G.; Harden, T. Kendall; Jacobson, Kenneth A.

2009-11-01

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

A Reinvestigation of the Dimer of para-Benzoquinone with Pyrimidine with MP2, CCSD(T) and DFT using Functionals including those Designed to Describe Dispersion

PubMed Central

Marianski, Mateusz; Oliva, Antoni

2012-01-01

We reevaluate the interaction of pyridine and p-benzoquinone using functionals designed to treat dispersion. We compare the relative energies of four different structures: stacked, T-shaped (identified for the first time) and two planar H-bonded geometries using these functionals (B97-D, ωB97x-D, M05, M05-2X, M06, M06L, M06-2X), other functionals (PBE1PBE, B3LYP, X3LYP), MP2 and CCSD(T) using basis sets as large as cc-pVTZ. The functionals designed to treat dispersion behave erratically as the predictions of the most stable structure vary considerably. MP2 predicts the experimentally observed structure (H-bonded) to be the least stable, while single point CCSD(T) at the MP2 optimized geometry correctly predicts the observed structure to be most stable. We have confirmed the assignment of the experimental structure using new calculations of the vibrational frequency shifts previously used to identify the structure. The MP2/cc-pVTZ vibrational calculations are in excellent agreement with the observations. All methods used to calculate the energies provide vibrational shifts that agree with the observed structure even though most do not predict this structure to be most stable. The implications for evaluating possible π-stacking in biologically important systems are discussed. PMID:22765283

A reinvestigation of the dimer of para-benzoquinone and pyrimidine with MP2, CCSD(T), and DFT using functionals including those designed to describe dispersion.

PubMed

Marianski, Mateusz; Oliva, Antoni; Dannenberg, J J

2012-08-02

We reevaluate the interaction of pyridine and p-benzoquinone using functionals designed to treat dispersion. We compare the relative energies of four different structures: stacked, T-shaped (identified for the first time), and two planar H-bonded geometries using these functionals (B97-D, ωB97x-D, M05, M05-2X, M06, M06L, and M06-2X), other functionals (PBE1PBE, B3LYP, X3LYP), MP2, and CCSD(T) using basis sets as large as cc-pVTZ. The functionals designed to treat dispersion behave erratically as the predictions of the most stable structure vary considerably. MP2 predicts the experimentally observed structure (H-bonded) to be the least stable, while single-point CCSD(T) at the MP2 optimized geometry correctly predicts the observed structure to be the most stable. We have confirmed the assignment of the experimental structure using new calculations of the vibrational frequency shifts previously used to identify the structure. The MP2/cc-pVTZ vibrational calculations are in excellent agreement with the observations. All methods used to calculate the energies provide vibrational shifts that agree with the observed structure even though most do not predict this structure to be most stable. The implications for evaluating possible π-stacking in biologically important systems are discussed.

3D-QSAR studies on 1,2,4-triazolyl 5-azaspiro [2.4]-heptanes as D3R antagonists

NASA Astrophysics Data System (ADS)

Zhang, Xin; Zhang, Hui

2018-07-01

Dopamine D3 receptor has become an attractive target in the treatment of abused drugs. 3D-QSAR studies were performed on a novel series of D3 receptor antagonists, 1,2,4-triazolyl 5-azaspiro [2.4]-heptanes, using CoMFA and CoMSIA methods. Two predictive 3D-QSAR models have been generated for the modified design of D3R antagonists. Based on the steric, electrostatic, hydrophobic and hydrogen-bond acceptor information of contour maps, key structural factors affecting the bioactivity were explored. This work gives helpful suggestions on the design of novel D3R antagonists with increased activities.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

X-ray Emission Spectroscopy in Magnetic 3d-Transition Metals

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

Iota, V; Park, J; Baer, B

2003-11-18

The application of high pressure affects the band structure and magnetic interactions in solids by modifying nearest-neighbor distances and interatomic potentials. While all materials experience electronic changes with increasing pressure, spin polarized, strongly electron correlated materials are expected to undergo the most dramatic transformations. In such materials, (d and f-electron metals and compounds), applied pressure reduces the strength of on-site correlations, leading to increased electron delocalization and, eventually, to loss of its magnetism. In this ongoing project, we study the electronic and magnetic properties of Group VIII, 3d (Fe, Co and Ni) magnetic transition metals and their compounds at highmore » pressures. The high-pressure properties of magnetic 3d-transition metals and compounds have been studied extensively over the years, because of iron being a major constituent of the Earth's core and its relevance to the planetary modeling to understand the chemical composition, internal structure, and geomagnetism. However, the fundamental scientific interest in the high-pressure properties of magnetic 3d-electron systems extends well beyond the geophysical applications to include the electron correlation-driven physics. The role of magnetic interactions in the stabilization of the ''non-standard'' ambient pressure structures of Fe, Co and Ni is still incompletely understood. Theoretical studies have predicted (and high pressure experiments are beginning to show) strong correlations between the electronic structure and phase stability in these materials. The phase diagrams of magnetic 3d systems reflect a delicate balance between spin interactions and structural configuration. At ambient conditions, the crystal structures of {alpha}-Fe(bcc) and {var_epsilon}-Co(hcp) phases depart from the standard sequence (hcp {yields} bcc{yields} hcp {yields} fcc), as observed in all other non-magnetic transition metals with increasing the d-band occupancy, and are different from those of their 4d- and 5d-counter parts. This anomalous behavior has been interpreted in terms of the spin-polarized d-band altering the d-band occupancy [1]. At high pressures, however, the d-valence band is expected to broaden resulting in a suppression or even a complete loss of magnetism. Experimentally, ferromagnetic {alpha}(bcc)-Fe has been confirmed to transform to non-magnetic {var_epsilon}-Fe (hcp) at 10 GPa [2,3]. Recently, we have also observed a similar transition in Co from ferromagnetic {alpha}(hcp)-Co to likely nonmagnetic {beta}(fcc)-Co at 105 GPa[4]. A similar structural phase transition is expected in Ni, probably in the second-order fcc-fcc transition. However, there has been no directly measured change in magnetism associated with the structural phase transition in Co, nor has yet been confirmed such an iso-structural phase transition in Ni. Similar electronic transitions have been proposed in these 3d-transition metal oxides (FeO, CoO and NiO) from high spin (magnetic) to low spin (nonmagnetic) states [5]. In each of these systems, the magnetic transition is accompanied by a first-order structural transition involving large volume collapse (10% in FeO, for example). So far, there have been no electronic measurements under pressure confirming these significant theoretical predictions, although the predicted pressures for the volume collapse transitions are within the experimental pressure range (80-200GPa).« less

Mapping Cortical Laminar Structure in the 3D BigBrain.

PubMed

Wagstyl, Konrad; Lepage, Claude; Bludau, Sebastian; Zilles, Karl; Fletcher, Paul C; Amunts, Katrin; Evans, Alan C

2018-07-01

Histological sections offer high spatial resolution to examine laminar architecture of the human cerebral cortex; however, they are restricted by being 2D, hence only regions with sufficiently optimal cutting planes can be analyzed. Conversely, noninvasive neuroimaging approaches are whole brain but have relatively low resolution. Consequently, correct 3D cross-cortical patterns of laminar architecture have never been mapped in histological sections. We developed an automated technique to identify and analyze laminar structure within the high-resolution 3D histological BigBrain. We extracted white matter and pial surfaces, from which we derived histologically verified surfaces at the layer I/II boundary and within layer IV. Layer IV depth was strongly predicted by cortical curvature but varied between areas. This fully automated 3D laminar analysis is an important requirement for bridging high-resolution 2D cytoarchitecture and in vivo 3D neuroimaging. It lays the foundation for in-depth, whole-brain analyses of cortical layering.

Evaluating the morphological completeness of a training image.

PubMed

Gao, Mingliang; Teng, Qizhi; He, Xiaohai; Feng, Junxi; Han, Xue

2017-05-01

Understanding the three-dimensional (3D) stochastic structure of a porous medium is helpful for studying its physical properties. A 3D stochastic structure can be reconstructed from a two-dimensional (2D) training image (TI) using mathematical modeling. In order to predict what specific morphology belonging to a TI can be reconstructed at the 3D orthogonal slices by the method of 3D reconstruction, this paper begins by introducing the concept of orthogonal chords. After analyzing the relationship among TI morphology, orthogonal chords, and the 3D morphology of orthogonal slices, a theory for evaluating the morphological completeness of a TI is proposed for the cases of three orthogonal slices and of two orthogonal slices. The proposed theory is evaluated using four TIs of porous media that represent typical but distinct morphological types. The significance of this theoretical evaluation lies in two aspects: It allows special morphologies, for which the attributes of a TI can be reconstructed at a special orthogonal slice of a 3D structure, to be located and quantified, and it can guide the selection of an appropriate reconstruction method for a special TI.

Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

PubMed

Pizarro, Ricardo A; Cheng, Xi; Barnett, Alan; Lemaitre, Herve; Verchinski, Beth A; Goldman, Aaron L; Xiao, Ena; Luo, Qian; Berman, Karen F; Callicott, Joseph H; Weinberger, Daniel R; Mattay, Venkata S

2016-01-01

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

Identifying Structure-Property Relationships Through DREAM.3D Representative Volume Elements and DAMASK Crystal Plasticity Simulations: An Integrated Computational Materials Engineering Approach

NASA Astrophysics Data System (ADS)

Diehl, Martin; Groeber, Michael; Haase, Christian; Molodov, Dmitri A.; Roters, Franz; Raabe, Dierk

2017-05-01

Predicting, understanding, and controlling the mechanical behavior is the most important task when designing structural materials. Modern alloy systems—in which multiple deformation mechanisms, phases, and defects are introduced to overcome the inverse strength-ductility relationship—give raise to multiple possibilities for modifying the deformation behavior, rendering traditional, exclusively experimentally-based alloy development workflows inappropriate. For fast and efficient alloy design, it is therefore desirable to predict the mechanical performance of candidate alloys by simulation studies to replace time- and resource-consuming mechanical tests. Simulation tools suitable for this task need to correctly predict the mechanical behavior in dependence of alloy composition, microstructure, texture, phase fractions, and processing history. Here, an integrated computational materials engineering approach based on the open source software packages DREAM.3D and DAMASK (Düsseldorf Advanced Materials Simulation Kit) that enables such virtual material development is presented. More specific, our approach consists of the following three steps: (1) acquire statistical quantities that describe a microstructure, (2) build a representative volume element based on these quantities employing DREAM.3D, and (3) evaluate the representative volume using a predictive crystal plasticity material model provided by DAMASK. Exemplarily, these steps are here conducted for a high-manganese steel.

Transverse Tensile Properties of 3 Dimension-4 Directional Braided Cf/SiC Composite Based on Double-Scale Model

NASA Astrophysics Data System (ADS)

Niu, Xuming; Sun, Zhigang; Song, Yingdong

2017-11-01

In this thesis, a double-scale model for 3 Dimension-4 directional(3D-4d) braided C/SiC composites(CMCs) has been proposed to investigate mechanical properties of it. The double-scale model involves micro-scale which takes fiber/matrix/porosity in fibers tows into consideration and the unit cell scale which considers the 3D-4d braiding structure. Basing on the Micro-optical photographs of composite, we can build a parameterized finite element model that reflects structure of 3D-4d braided composites. The mechanical properties of fiber tows in transverse direction are studied by combining the crack band theory for matrix cracking and cohesive zone model for interface debonding. Transverse tensile process of 3D-4d CMCs can be simulated by introducing mechanical properties of fiber tows into finite element of 3D-4d braided CMCs. Quasi-static tensile tests of 3D-4d braided CMCs have been performed with PWS-100 test system. The predicted tensile stress-strain curve by the double scale model finds good agreement with the experimental results.

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

Measurements of d 2 n and A 1 n : Probing the neutron spin structure

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

Flay, D.; Posik, M.; Parno, D. S.

We report on the results of the E06-014 experiment performed at Jefferson Lab in Hall A, where a precision measurement of the twist-3 matrix element d(2) of the neutron (d(2)(n)) was conducted. The quantity d(2)(n) represents the average color Lorentz force a struck quark experiences in a deep inelastic electron scattering event off a neutron due to its interaction with the hadronizing remnants. This color force was determined from a linear combination of the third moments of the He-3 spin structure functions, g(1) and g(2), after nuclear corrections had been applied to these moments. The structure functions were obtained frommore » a measurement of the unpolarized cross section and of double-spin asymmetries in the scattering of a longitudinally polarized electron beam from a transversely and a longitudinally polarized He-3 target. The measurement kinematics included two average Q(2) bins of 3.2 GeV2 and 4.3 GeV2, and Bjorken-x 0.25 <= x <= 0.90 covering the deep inelastic and resonance regions. We have found that d(2)(n) is small and negative for < Q(2)> = 3.2 GeV2, and even smaller for < Q(2)> = 4.3 GeV2, consistent with the results of a lattice QCD calculation. The twist-4 matrix element f(2)(n) was extracted by combining our measured d(2)(n) with the world data on the first moment in x of g(1)(n), Gamma(n)(1). We found f(2)(n) to be roughly an order of magnitude larger than d(2)(n). Utilizing the extracted d(2)(n) and f(2)(n) data, we separated the Lorentz color force into its electric and magnetic components, F-E(y,n) and F-B(y,n), and found them to be equal and opposite in magnitude, in agreement with the predictions from an instanton model but not with those from QCD sum rules. Furthermore, using the measured double-spin asymmetries, we have extracted the virtual photon-nucleon asymmetry on the neutron A(1)(n), the structure function ratio g(1)(n)/F-1(n), and the quark ratios (Delta u + Delta(u) over bar)/(u + (u) over bar) and (Delta d + Delta(d) over bar)/(d + (d) over bar). These results were found to be consistent with deep-inelastic scattering world data and with the prediction of the constituent quark model but at odds with the perturbative quantum chromodynamics predictions at large x.« less

Multiphase flow predictions from carbonate pore space images using extracted network models

NASA Astrophysics Data System (ADS)

Al-Kharusi, Anwar S.; Blunt, Martin J.

2008-06-01

A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.

Chinks in Solar Dynamo Theory: Turbulent Diffusion, Dynamo Waves and Magnetic Helicity

NASA Technical Reports Server (NTRS)

DeLuca, E. E.; Hurlburt, N.

1998-01-01

In this first year of our investigation we explored the role of compressibility and stratification in the dissipation of magnetic fields. The predictions of Mean Field Electrodynamics have been questioned because of the strong feedback of small scale magnetic structure on the velocity fields. In 2-D, this nonlinear feedback results in a lengthening of the turbulent decay time. In 3-D alpha-quenching is predicted. Previous studies assumed a homogeneous fluid. This first year we present recent results from 2-D compressible MHD decay simulations in a highly stratified atmosphere that more closely resembles to solar convection zone. We have applied for NCCS T3E time to assist in the performance of our 3-D calculations.

Sequence analysis, structure prediction and functional validation of phaC1/phaC2 genes of Pseudomonas sp. LDC-25 and its importance in polyhydroxyalkanoate accumulation

USDA-ARS?s Scientific Manuscript database

Polyhydroxyalkanoates (PHAs) are attractive biomaterials in both conventional medical devices and tissue engineering. PHA synthase is responsible for catalyzing the formation of polyhydroxyalkanoates (PHA), but its structural information is limited. Hence, the focus of this study is to predict 3D mo...

Active sites prediction and binding analysis E1-E2 protein human papillomavirus with biphenylsulfonacetic acid

NASA Astrophysics Data System (ADS)

Iryani, I.; Amelia, F.; Iswendi, I.

2018-04-01

Cervix cancer triggered by Human papillomavirus infection is the second cause to woman death in worldwide. The binding site of E1-E2 protein of HPV 16 is not known from a 3-D structure yet, so in this study we address this issue to study the structure of E1-E2 protein from Human papillomavirus type 16 and to find its potential binding sites using biphenylsulfonacetic acid as inhibitor. Swiss model was used for 3D structure prediction and PDB: 2V9P (E1 protein) and 2NNU (E2 protein) having 52.32% and 100% identity respectively was selected as a template. The 3D model structure developed of E1 and E2 in the core and allowed regions were 99.2% and 99.5%. The ligand binding sites were predicted using online server meta pocket 2.0 and MOE 2009.10 was used for docking. E1-and E2 protein of HPV-16 has three potential binding site that can interact with the inhibitors. The Docking biphenylsulfonacetic acid using these binding sites shows that ligand interact with the protein through hydrogen bonds on Lys 403, Arg 410, His 551 in the first pocket, on Tyr 32, Leu 99 in the second pocket, and Lys 558m Lys 517 in the third pocket.

A matrix-free implicit unstructured multigrid finite volume method for simulating structural dynamics and fluid structure interaction

NASA Astrophysics Data System (ADS)

Lv, X.; Zhao, Y.; Huang, X. Y.; Xia, G. H.; Su, X. H.

2007-07-01

A new three-dimensional (3D) matrix-free implicit unstructured multigrid finite volume (FV) solver for structural dynamics is presented in this paper. The solver is first validated using classical 2D and 3D cantilever problems. It is shown that very accurate predictions of the fundamental natural frequencies of the problems can be obtained by the solver with fast convergence rates. This method has been integrated into our existing FV compressible solver [X. Lv, Y. Zhao, et al., An efficient parallel/unstructured-multigrid preconditioned implicit method for simulating 3d unsteady compressible flows with moving objects, Journal of Computational Physics 215(2) (2006) 661-690] based on the immersed membrane method (IMM) [X. Lv, Y. Zhao, et al., as mentioned above]. Results for the interaction between the fluid and an immersed fixed-free cantilever are also presented to demonstrate the potential of this integrated fluid-structure interaction approach.

From molecular to macroscopic via the rational design of a self-assembled 3D DNA crystal.

PubMed

Zheng, Jianping; Birktoft, Jens J; Chen, Yi; Wang, Tong; Sha, Ruojie; Constantinou, Pamela E; Ginell, Stephan L; Mao, Chengde; Seeman, Nadrian C

2009-09-03

We live in a macroscopic three-dimensional (3D) world, but our best description of the structure of matter is at the atomic and molecular scale. Understanding the relationship between the two scales requires a bridge from the molecular world to the macroscopic world. Connecting these two domains with atomic precision is a central goal of the natural sciences, but it requires high spatial control of the 3D structure of matter. The simplest practical route to producing precisely designed 3D macroscopic objects is to form a crystalline arrangement by self-assembly, because such a periodic array has only conceptually simple requirements: a motif that has a robust 3D structure, dominant affinity interactions between parts of the motif when it self-associates, and predictable structures for these affinity interactions. Fulfilling these three criteria to produce a 3D periodic system is not easy, but should readily be achieved with well-structured branched DNA motifs tailed by sticky ends. Complementary sticky ends associate with each other preferentially and assume the well-known B-DNA structure when they do so; the helically repeating nature of DNA facilitates the construction of a periodic array. It is essential that the directions of propagation associated with the sticky ends do not share the same plane, but extend to form a 3D arrangement of matter. Here we report the crystal structure at 4 A resolution of a designed, self-assembled, 3D crystal based on the DNA tensegrity triangle. The data demonstrate clearly that it is possible to design and self-assemble a well-ordered macromolecular 3D crystalline lattice with precise control.

A 2.5-dimensional method for the prediction of structure-borne low-frequency noise from concrete rail transit bridges.

PubMed

Li, Qi; Song, Xiaodong; Wu, Dingjun

2014-05-01

Predicting structure-borne noise from bridges subjected to moving trains using the three-dimensional (3D) boundary element method (BEM) is a time consuming process. This paper presents a two-and-a-half dimensional (2.5D) BEM-based procedure for simulating bridge-borne low-frequency noise with higher efficiency, yet no loss of accuracy. The two-dimensional (2D) BEM of a bridge with a constant cross section along the track direction is adopted to calculate the spatial modal acoustic transfer vectors (MATVs) of the bridge using the space-wave number transforms of its 3D modal shapes. The MATVs calculated using the 2.5D method are then validated by those computed using the 3D BEM. The bridge-borne noise is finally obtained through the MATVs and modal coordinate responses of the bridge, considering time-varying vehicle-track-bridge dynamic interaction. The presented procedure is applied to predict the sound pressure radiating from a U-shaped concrete bridge, and the computed results are compared with those obtained from field tests on Shanghai rail transit line 8. The numerical results match well with the measured results in both time and frequency domains at near-field points. Nevertheless, the computed results are smaller than the measured ones for far-field points, mainly due to the sound radiation from adjacent spans neglected in the current model.

Metallic behavior in the graphene analogue Ni 3(HITP) 2 and a strategy to render the material a semiconductor.

DOE PAGES

Foster, Michael E.; Sohlberg, Karl; Spataru, Dan Catalin; ...

2016-06-19

The metal organic framework material Ni 3(2,3,6,7,10,11 - hexaiminotriphenylene) 2, (Ni 3(HITP) 2) is composed of layers of extended conjugated planes analogous to graphene. We carried out Density functional theory (DFT) calculations to model the electronic structure of bulk and monolayer Ni 3(HITP) 2. The layered 3D material is metallic, similar to graphene. Our calculations predict that there is appreciable band dispersion not only in-plane, but perpendicular to the stacking planes as well, suggesting that, unlike graphene, the conductivity may be nearly isotropic. In contrast, a 2D monolayer of the material exhibits a band gap, consistent with previously published results.more » Insight obtained from studies of the evolution of the material from semiconducting to metallic as the material is transitioned from 2D to 3D suggests the possibility of modifying the material to render it semiconducting by changing the metal center and inserting spacer moieties between the layers. Furthermore, the DFT calculations predict that the modified material will be structurally stable and exhibit a band gap.« less

Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

PubMed Central

2010-01-01

Background In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA. Results Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection. Discussion The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction. PMID:20550657

Periodic Forced Response of Structures Having Three-Dimensional Frictional Constraints

NASA Astrophysics Data System (ADS)

CHEN, J. J.; YANG, B. D.; MENQ, C. H.

2000-01-01

Many mechanical systems have moving components that are mutually constrained through frictional contacts. When subjected to cyclic excitations, a contact interface may undergo constant changes among sticks, slips and separations, which leads to very complex contact kinematics. In this paper, a 3-D friction contact model is employed to predict the periodic forced response of structures having 3-D frictional constraints. Analytical criteria based on this friction contact model are used to determine the transitions among sticks, slips and separations of the friction contact, and subsequently the constrained force which consists of the induced stick-slip friction force on the contact plane and the contact normal load. The resulting constrained force is often a periodic function and can be considered as a feedback force that influences the response of the constrained structures. By using the Multi-Harmonic Balance Method along with Fast Fourier Transform, the constrained force can be integrated with the receptance of the structures so as to calculate the forced response of the constrained structures. It results in a set of non-linear algebraic equations that can be solved iteratively to yield the relative motion as well as the constrained force at the friction contact. This method is used to predict the periodic response of a frictionally constrained 3-d.o.f. oscillator. The predicted results are compared with those of the direct time integration method so as to validate the proposed method. In addition, the effect of super-harmonic components on the resonant response and jump phenomenon is examined.

Dirac cones in artificial structures of 3d transitional-metals doped Mg-Al spinels

NASA Astrophysics Data System (ADS)

Lu, Yuan; Feng, Min; Shao, Bin; Zuo, Xu

2014-05-01

Motivated by recent theoretical predications for Dirac cone in two-dimensional (2D) triangular lattice [H. Ishizuka, Phys. Rev. Lett. 109, 237207 (2012)], first-principles studies are performed to predict Dirac cones in artificial structures of 3d transitional-metals (TM = Ti, V, Cr, Mn, Fe, Co, Ni, and Cu) doped Mg-Al spinels. In investigated artificial structures, TM dopants substitute specific positions of the B sub-lattice in Mg-Al spinel, and form a quasi-2D triangular lattice in the a-b plane. Calculated results illustrate the existence of the spin-polarized Dirac cones formed in d-wave bands at (around) the K-point in the momentum space. The study provides a promising route for engineering Dirac physics in condensed matters.

Disruption of sheet-like structures in Alfvénic turbulence by magnetic reconnection

NASA Astrophysics Data System (ADS)

Mallet, A.; Schekochihin, A. A.; Chandran, B. D. G.

2017-07-01

We propose a mechanism whereby the intense, sheet-like structures naturally formed by dynamically aligning Alfvénic turbulence are destroyed by magnetic reconnection at a scale \\hat{λ }_D, larger than the dissipation scale predicted by models of intermittent, dynamically aligning turbulence. The reconnection process proceeds in several stages: first, a linear tearing mode with N magnetic islands grows and saturates, and then the X-points between these islands collapse into secondary current sheets, which then reconnect until the original structure is destroyed. This effectively imposes an upper limit on the anisotropy of the structures within the perpendicular plane, which means that at scale \\hat{λ }_D the turbulent dynamics change: at scales larger than \\hat{λ }_D, the turbulence exhibits scale-dependent dynamic alignment and a spectral index approximately equal to -3/2, while at scales smaller than \\hat{λ }_D, the turbulent structures undergo a succession of disruptions due to reconnection, limiting dynamic alignment, steepening the effective spectral index and changing the final dissipation scale. The scaling of \\hat{λ }_D with the Lundquist (magnetic Reynolds) number S_{L_\\perp } depends on the order of the statistics being considered, and on the specific model of intermittency; the transition between the two regimes in the energy spectrum is predicted at approximately \\hat{λ }_D˜ S_{L_\\perp }^{-0.6}. The spectral index below \\hat{λ }_D is bounded between -5/3 and -2.3. The final dissipation scale is at \\hat{λ }_{η ,∞}˜ S_{L_\\perp }^{-3/4}, the same as the Kolmogorov scale arising in theories of turbulence that do not involve scale-dependent dynamic alignment.

Two-dimensional wide-band-gap II-V semiconductors with a dilated graphene-like structure

NASA Astrophysics Data System (ADS)

Zhang, Xue-Jing; Liu, Bang-Gui

2016-12-01

Since the advent of graphene, two-dimensional (2D) materials have become very attractive and there is growing interest in exploring new 2D materials beyond graphene. Here, through density-functional theory (DFT) calculations, we predict 2D wide-band-gap II-V semiconductor materials of M3X2 (M = Zn, Cd and X = N, P, As) with a dilated graphene-like honeycomb structure. In this structure the group-V X atoms form two X-atomic planes symmetrically astride the centering group-IIB M atomic plane. Our DFT calculation shows that 2D Zn3N2, Zn3P2 and Zn3As2 have direct band gaps of 2.87, 3.81 and 3.55 eV, respectively, and 2D Cd3N2, Cd3P2 and Cd3As2 exhibit indirect band gaps of 2.74, 3.51 and 3.29 eV, respectively. Each of the six 2D materials is shown to have effective carrier (either hole or electron) masses down to 0.03m 0-0.05m 0. The structural stability and feasibility of experimental realization of these 2D materials has been shown in terms of DFT phonon spectra and total energy comparison with related existing bulk materials. On the experimental side, there already are many similar two-coordinate structures of Zn and other transition metals in various organic materials. Therefore, these 2D semiconductors can enrich the family of 2D electronic materials and may have promising potential for achieving novel transistors and optoelectronic devices.

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Structural Revisions of a Class of Natural Products: Scaffolds of Aglycon Analogues of Fusicoccins and Cotylenins Isolated from Fungi.

PubMed

Tang, Ying; Xue, Yongbo; Du, Guang; Wang, Jianping; Liu, Junjun; Sun, Bin; Li, Xiao-Nian; Yao, Guangmin; Luo, Zengwei; Zhang, Yonghui

2016-03-14

The reisolation and structural revision of brassicicene D is described, and inspired us to reassign the core skeletons of brassicicenes C-H, J and K, ranging from dicyclopenta[a,d]cyclooctane to tricyclo[9.2.1.0(3,7)]tetradecane using quantum-chemical predictions and experimental validation strategies. Three novel, highly modified fusicoccanes, brassicicenes L-N, were also isolated from the fungus Alternaria brassicicola, and their structures were unequivocally established by spectroscopic data, ECD calculations, and crystallography. The reassigned structures represent the first class of bridgehead double-bond-containing natural products with a bicyclo[6.2.1]undecane carbon skeleton. Furthermore, their stabilities were first predicted with olefin strain energy calculations. Collectively, these findings extend our view of the application of computational predictions and biosynthetic logic-based structure elucidation to address problems related to the structure and stability of natural products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

LCS-TA to identify similar fragments in RNA 3D structures.

PubMed

Wiedemann, Jakub; Zok, Tomasz; Milostan, Maciej; Szachniuk, Marta

2017-10-23

In modern structural bioinformatics, comparison of molecular structures aimed to identify and assess similarities and differences between them is one of the most commonly performed procedures. It gives the basis for evaluation of in silico predicted models. It constitutes the preliminary step in searching for structural motifs. In particular, it supports tracing the molecular evolution. Faced with an ever-increasing amount of available structural data, researchers need a range of methods enabling comparative analysis of the structures from either global or local perspective. Herein, we present a new, superposition-independent method which processes pairs of RNA 3D structures to identify their local similarities. The similarity is considered in the context of structure bending and bonds' rotation which are described by torsion angles. In the analyzed RNA structures, the method finds the longest continuous segments that show similar torsion within a user-defined threshold. The length of the segment is provided as local similarity measure. The method has been implemented as LCS-TA algorithm (Longest Continuous Segments in Torsion Angle space) and is incorporated into our MCQ4Structures application, freely available for download from http://www.cs.put.poznan.pl/tzok/mcq/ . The presented approach ties torsion-angle-based method of structure analysis with the idea of local similarity identification by handling continuous 3D structure segments. The first method, implemented in MCQ4Structures, has been successfully utilized in RNA-Puzzles initiative. The second one, originally applied in Euclidean space, is a component of LGA (Local-Global Alignment) algorithm commonly used in assessing protein models submitted to CASP. This unique combination of concepts implemented in LCS-TA provides a new perspective on structure quality assessment in local and quantitative aspect. A series of computational experiments show the first results of applying our method to comparison of RNA 3D models. LCS-TA can be used for identifying strengths and weaknesses in the prediction of RNA tertiary structures.

Contrast model for three-dimensional vehicles in natural lighting and search performance analysis

NASA Astrophysics Data System (ADS)

Witus, Gary; Gerhart, Grant R.; Ellis, R. Darin

2001-09-01

Ground vehicles in natural lighting tend to have significant and systematic variation in luminance through the presented area. This arises, in large part, from the vehicle surfaces having different orientations and shadowing relative to the source of illumination and the position of the observer. These systematic differences create the appearance of a structured 3D object. The 3D appearance is an important factor in search, figure-ground segregation, and object recognition. We present a contrast metric to predict search and detection performance that accounts for the 3D structure. The approach first computes the contrast of the front (or rear), side, and top surfaces. The vehicle contrast metric is the area-weighted sum of the absolute values of the contrasts of the component surfaces. The 3D structure contrast metric, together with target height, account for more than 80% of the variance in probability of detection and 75% of the variance in search time. When false alarm effects are discounted, they account for 89% of the variance in probability of detection and 95% of the variance in search time. The predictive power of the signature metric, when calibrated to half the data and evaluated against the other half, is 90% of the explanatory power.

Tertiary model of a plant cellulose synthase

PubMed Central

Sethaphong, Latsavongsakda; Haigler, Candace H.; Kubicki, James D.; Zimmer, Jochen; Bonetta, Dario; DeBolt, Seth; Yingling, Yaroslava G.

2013-01-01

A 3D atomistic model of a plant cellulose synthase (CESA) has remained elusive despite over forty years of experimental effort. Here, we report a computationally predicted 3D structure of 506 amino acids of cotton CESA within the cytosolic region. Comparison of the predicted plant CESA structure with the solved structure of a bacterial cellulose-synthesizing protein validates the overall fold of the modeled glycosyltransferase (GT) domain. The coaligned plant and bacterial GT domains share a six-stranded β-sheet, five α-helices, and conserved motifs similar to those required for catalysis in other GT-2 glycosyltransferases. Extending beyond the cross-kingdom similarities related to cellulose polymerization, the predicted structure of cotton CESA reveals that plant-specific modules (plant-conserved region and class-specific region) fold into distinct subdomains on the periphery of the catalytic region. Computational results support the importance of the plant-conserved region and/or class-specific region in CESA oligomerization to form the multimeric cellulose–synthesis complexes that are characteristic of plants. Relatively high sequence conservation between plant CESAs allowed mapping of known mutations and two previously undescribed mutations that perturb cellulose synthesis in Arabidopsis thaliana to their analogous positions in the modeled structure. Most of these mutation sites are near the predicted catalytic region, and the confluence of other mutation sites supports the existence of previously undefined functional nodes within the catalytic core of CESA. Overall, the predicted tertiary structure provides a platform for the biochemical engineering of plant CESAs. PMID:23592721

Capillary Origami Inspired Fabrication of Complex 3D Hydrogel Constructs.

PubMed

Li, Moxiao; Yang, Qingzhen; Liu, Hao; Qiu, Mushu; Lu, Tian Jian; Xu, Feng

2016-09-01

Hydrogels have found broad applications in various engineering and biomedical fields, where the shape and size of hydrogels can profoundly influence their functions. Although numerous methods have been developed to tailor 3D hydrogel structures, it is still challenging to fabricate complex 3D hydrogel constructs. Inspired by the capillary origami phenomenon where surface tension of a droplet on an elastic membrane can induce spontaneous folding of the membrane into 3D structures along with droplet evaporation, a facile strategy is established for the fabrication of complex 3D hydrogel constructs with programmable shapes and sizes by crosslinking hydrogels during the folding process. A mathematical model is further proposed to predict the temporal structure evolution of the folded 3D hydrogel constructs. Using this model, precise control is achieved over the 3D shapes (e.g., pyramid, pentahedron, and cube) and sizes (ranging from hundreds of micrometers to millimeters) through tuning membrane shape, dimensionless parameter of the process (elastocapillary number Ce ), and evaporation time. This work would be favorable to multiple areas, such as flexible electronics, tissue regeneration, and drug delivery. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Three dimensional quantitative structure-toxicity relationship modeling and prediction of acute toxicity for organic contaminants to algae.

PubMed

Jin, Xiangqin; Jin, Minghao; Sheng, Lianxi

2014-08-01

Although numerous chemicals have been identified to have significant toxicological effect on aquatic organisms, there is still lack of a reliable, high-throughput approach to evaluate, screen and monitor the presence of organic contaminants in aquatic system. In the current study, we proposed a synthetic pipeline to automatically model and predict the acute toxicity of chemicals to algae. In the procedure, a new alignment-free three dimensional (3D) structure characterization method was described and, with this method, several 3D-quantitative structure-toxicity relationship (3D-QSTR) models were developed, from which two were found to exhibit strong internal fitting ability and high external predictive power. The best model was established by Gaussian process (GP), which was further employed to perform extrapolation on a random compound library consisting of 1014 virtually generated substituted benzenes. It was found that (i) substitution number can only exert slight influence on chemical׳s toxicity, but low-substituted benzenes seem to have higher toxicity than those of high-substituted entities, and (ii) benzenes substituted by nitro group and halogens exhibit high acute toxicity as compared to other substituents such as methyl and carboxyl groups. Subsequently, several promising candidates suggested by computational prediction were assayed by using a standard algal growth inhibition test. Consequently, four substituted benzenes, namely 2,3-dinitrophenol, 2-chloro-4-nitroaniline, 1,2,3-trinitrobenzene and 3-bromophenol, were determined to have high acute toxicity to Scenedesmus obliquus, with their EC50 values of 2.5±0.8, 10.5±2.1, 1.4±0.2 and 42.7±5.4μmol/L, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Protein structure modeling and refinement by global optimization in CASP12.

PubMed

Hong, Seung Hwan; Joung, InSuk; Flores-Canales, Jose C; Manavalan, Balachandran; Cheng, Qianyi; Heo, Seungryong; Kim, Jong Yun; Lee, Sun Young; Nam, Mikyung; Joo, Keehyoung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded. © 2017 Wiley Periodicals, Inc.

Prediction of a common beta-propeller catalytic domain for fructosyltransferases of different origin and substrate specificity.

PubMed

Pons, T; Hernández, L; Batista, F R; Chinea, G

2000-11-01

The three-dimensional (3D) structure of fructan biosynthetic enzymes is still unknown. Here, we have explored folding similarities between reported microbial and plant enzymes that catalyze transfructosylation reactions. A sequence-structure compatibility search using TOPITS, SDP, 3D-PSSM, and SAM-T98 programs identified a beta-propeller fold with scores above the confidence threshold that indicate a structurally conserved catalytic domain in fructosyltransferases (FTFs) of diverse origin and substrate specificity. The predicted fold appeared related to that of neuraminidase and sialidase, of glycoside hydrolase families 33 and 34, respectively. The most reliable structural model was obtained using the crystal structure of neuraminidase (Protein Data Bank file: 5nn9) as template, and it is consistent with the location of previously identified functional residues of bacterial levansucrases (Batista et al., 1999; Song & Jacques, 1999). The sequence-sequence analysis presented here reinforces the recent inclusion of fungal and plant FTFs into glycoside hydrolase family 32, and suggests a modified sequence pattern H-x (2)-[PTV]-x (4)-[LIVMA]-[NSCAYG]-[DE]-P-[NDSC][GA]3 for this family.

Prediction of a common beta-propeller catalytic domain for fructosyltransferases of different origin and substrate specificity.

PubMed Central

Pons, T.; Hernández, L.; Batista, F. R.; Chinea, G.

2000-01-01

The three-dimensional (3D) structure of fructan biosynthetic enzymes is still unknown. Here, we have explored folding similarities between reported microbial and plant enzymes that catalyze transfructosylation reactions. A sequence-structure compatibility search using TOPITS, SDP, 3D-PSSM, and SAM-T98 programs identified a beta-propeller fold with scores above the confidence threshold that indicate a structurally conserved catalytic domain in fructosyltransferases (FTFs) of diverse origin and substrate specificity. The predicted fold appeared related to that of neuraminidase and sialidase, of glycoside hydrolase families 33 and 34, respectively. The most reliable structural model was obtained using the crystal structure of neuraminidase (Protein Data Bank file: 5nn9) as template, and it is consistent with the location of previously identified functional residues of bacterial levansucrases (Batista et al., 1999; Song & Jacques, 1999). The sequence-sequence analysis presented here reinforces the recent inclusion of fungal and plant FTFs into glycoside hydrolase family 32, and suggests a modified sequence pattern H-x (2)-[PTV]-x (4)-[LIVMA]-[NSCAYG]-[DE]-P-[NDSC][GA]3 for this family. PMID:11305239

Experimental transient and permanent deformation studies of steel-sphere-impacted or explosively-impulsed aluminum panels

NASA Technical Reports Server (NTRS)

Witmer, E. A.; Merlis, F.; Rodal, J. J. A.; Stagliano, T. R.

1977-01-01

The sheet explosive loading technique (SELT) was employed to obtain elastic-plastic, large deflection 3-d transient and/or permanent strain data on simple well defined structural specimens and materials: initially-flat 6061-T651 aluminum panels with all four sides ideally clamped via integral construction. The SELT loading technique was chosen since it is both convenient and provides "forcing function information" of small uncertainty. These data will be useful for evaluating pertinent 3-d structural response prediction methods.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

PubMed

Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The impact of lateral variations in lithospheric thickness on glacial isostatic adjustment in West Antarctica

NASA Astrophysics Data System (ADS)

Nield, Grace A.; Whitehouse, Pippa L.; van der Wal, Wouter; Blank, Bas; O'Donnell, John Paul; Stuart, Graham W.

2018-04-01

Differences in predictions of Glacial Isostatic Adjustment (GIA) for Antarctica persist due to uncertainties in deglacial history and Earth rheology. The Earth models adopted in many GIA studies are defined by parameters that vary in the radial direction only and represent a global average Earth structure (referred to as 1D Earth models). Over-simplifying actual Earth structure leads to bias in model predictions in regions where Earth parameters differ significantly from the global average, such as West Antarctica. We investigate the impact of lateral variations in lithospheric thickness on GIA in Antarctica by carrying out two experiments that use different rheological approaches to define 3D Earth models that include spatial variations in lithospheric thickness. The first experiment defines an elastic lithosphere with spatial variations in thickness inferred from seismic studies. We compare the results from this 3D model with results derived from a 1D Earth model that has a uniform lithospheric thickness defined as the average of the 3D lithospheric thickness. Irrespective of deglacial history and sub-lithospheric mantle viscosity, we find higher gradients of present-day uplift rates (i.e. higher amplitude and shorter wavelength) in West Antarctica when using the 3D models, due to the thinner-than-1D-average lithosphere prevalent in this region. The second experiment uses seismically-inferred temperature as input to a power-law rheology thereby allowing the lithosphere to have a viscosity structure. Modelling the lithosphere with a power-law rheology results in behaviour that is equivalent to a thinner-lithosphere model, and it leads to higher amplitude and shorter wavelength deformation compared with the first experiment. We conclude that neglecting spatial variations in lithospheric thickness in GIA models will result in predictions of peak uplift and subsidence that are biased low in West Antarctica. This has important implications for ice-sheet modelling studies as the steeper gradients of uplift predicted from the more realistic 3D model may promote stability in marine-grounded regions of West Antarctica. Including lateral variations in lithospheric thickness, at least to the level of considering West and East Antarctica separately, is important for capturing short wavelength deformation and it has the potential to provide a better fit to GPS observations as well as an improved GIA correction for GRACE data.

Current and Future Tests of the Algebraic Cluster Model of12C

NASA Astrophysics Data System (ADS)

Gai, Moshe

2017-07-01

A new theoretical approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts, in12C, rotation-vibration structure with rotational bands of an oblate equilateral triangular symmetric spinning top with a D 3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with a degenerate 4+ and 4- (parity doublet) states. Our newly measured {2}2+ state in12C allows the first study of rotation-vibration structure in12C. The newly measured 5- state and 4- states fit very well the predicted ground state rotational band structure with the predicted sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a D 3h symmetry is characteristic of triatomic molecules, but it is observed in the ground state rotational band of12C for the first time in a nucleus. We discuss predictions of the ACM of other rotation-vibration bands in12C such as the (0+) Hoyle band and the (1-) bending mode with prediction of (“missing 3- and 4-”) states that may shed new light on clustering in12C and light nuclei. In particular, the observation (or non observation) of the predicted (“missing”) states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.6542 MeV in12C. We discuss proposed research programs at the Darmstadt S- DALINAC and at the newly constructed ELI-NP facility near Bucharest to test the predictions of the ACM in isotopes of carbon.

Molecular docking and QSAR study on steroidal compounds as aromatase inhibitors.

PubMed

Dai, Yujie; Wang, Qiang; Zhang, Xiuli; Jia, Shiru; Zheng, Heng; Feng, Dacheng; Yu, Peng

2010-12-01

In order to develop more potent, selective and less toxic steroidal aromatase (AR) inhibitors, molecular docking, 2D and 3D hybrid quantitative structure-activity relationship (QSAR) study have been conducted using topological, molecular shape, spatial, structural and thermodynamic descriptors on 32 steroidal compounds. The molecular docking study shows that one or more hydrogen bonds with MET374 are one of the essential requirements for the optimum binding of ligands. The QSAR model obtained indicates that the aromatase inhibitory activity can be enhanced by increasing SIC, SC_3_C, Jurs_WNSA_1, Jurs_WPSA_1 and decreasing CDOCKER interaction energy (ECD), IAC_Total and Shadow_XZfrac. The predicted results shows that this model has a comparatively good predictive power which can be used in prediction of activity of new steroidal aromatase inhibitors. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Prediction of p38 map kinase inhibitory activity of 3, 4-dihydropyrido [3, 2-d] pyrimidone derivatives using an expert system based on principal component analysis and least square support vector machine

PubMed Central

Shahlaei, M.; Saghaie, L.

2014-01-01

A quantitative structure–activity relationship (QSAR) study is suggested for the prediction of biological activity (pIC50) of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors. Modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (PCA) and least square support vector machine (LS-SVM) methods. The results showed that the pIC50 values calculated by LS-SVM are in good agreement with the experimental data, and the performance of the LS-SVM regression model is superior to the PCA-based model. The developed LS-SVM model was applied for the prediction of the biological activities of pyrimidone derivatives, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.460 for LS-SVM. The study provided a novel and effective approach for predicting biological activities of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors and disclosed that LS-SVM can be used as a powerful chemometrics tool for QSAR studies. PMID:26339262

Crystal field analysis of the energy level structure of Cs2NaAlF6:Cr3+

NASA Astrophysics Data System (ADS)

Rudowicz, C.; Brik, M. G.; Avram, N. M.; Yeung, Y. Y.; Gnutek, P.

2006-06-01

An analysis of the energy level structure of Cr3+ ions in Cs2NaAlF6 crystal is performed using the exchange charge model (ECM) together with the crystal field analysis/microscopic spin Hamiltonian (CFA/MSH) computer package. Utilizing the crystal structure data, our approach enables modelling of the crystal field parameters (CFPs) and thus the energy level structure for Cr3+ ions at the two crystallographically inequivalent sites in Cs2NaAlF6. Using the ECM initial adjustment procedure, the CFPs are calculated in the crystallographic axis system centred at the Cr3+ ion at each site. Additionally the CFPs are also calculated using the superposition model (SPM). The ECM and SPM predicted CFP values match very well. Consideration of the symmetry aspects for the so-obtained CFP datasets reveals that the latter axis system matches the symmetry-adapted axis system related directly to the six Cr-F bonds well. Using the ECM predicted CFPs as an input for the CFA/MSH package, the complete energy level schemes are calculated for Cr3+ ions at the two sites. Comparison of the theoretical results with the experimental spectroscopic data yields satisfactory agreement. Our results confirm that the actual symmetry at both impurity sites I and II in the Cs2NaAlF6:Cr3+ system is trigonal D3d. The ECM predicted CFPs may be used as the initial (starting) parameters for simulations and fittings of the energy levels for Cr3+ ions in structurally similar hosts.

Modeling local structure using crystal field and spin Hamiltonian parameters: the tetragonal FeK3+-OI2- defect center in KTaO3 crystal

NASA Astrophysics Data System (ADS)

Gnutek, P.; Y Yang, Z.; Rudowicz, C.

2009-11-01

The local structure and the spin Hamiltonian (SH) parameters, including the zero-field-splitting (ZFS) parameters D and (a+2F/3), and the Zeeman g factors g_{\\parallel } and g_{\\perp } , are theoretically investigated for the FeK3+-OI2- center in KTaO3 crystal. The microscopic SH (MSH) parameters are modeled within the framework of the crystal field (CF) theory employing the CF analysis (CFA) package, which also incorporates the MSH modules. Our approach takes into account the spin-orbit interaction as well as the spin-spin and spin-other-orbit interactions omitted in previous studies. The superposition model (SPM) calculations are carried out to provide input CF parameters for the CFA/MSH package. The combined SPM-CFA/MSH approach is used to consider various structural models for the FeK3+-OI2- defect center in KTaO3. This modeling reveals that the off-center displacement of the Fe3+ ions, Δ1(Fe3+), combined with an inward relaxation of the nearest oxygen ligands, Δ2(O2-), and the existence of the interstitial oxygen OI2- give rise to a strong tetragonal crystal field. This finding may explain the large ZFS experimentally observed for the FeK3+-OI2- center in KTaO3. Matching the theoretical MSH predictions with the available structural data as well as electron magnetic resonance (EMR) and optical spectroscopy data enables predicting reasonable ranges of values of Δ1(Fe3+) and Δ2(O2-) as well as the possible location of OI2- ligands around Fe3+ ions in KTaO3. The defect structure model obtained using the SPM-CFA/MSH approach reproduces very well the ranges of the experimental SH parameters D, g_{\\parallel } and g_{\\perp } and importantly yields not only the correct magnitude of D but also the sign, unlike previous studies. More reliable predictions may be achieved when experimental data on (a+2F/3) and/or crystal field energy levels become available. Comparison of our results with those arising from alternative models existing in the literature indicates considerable advantages of our method and presumably higher reliability of our predictions.

Tidal Energy: The benthic effects of an operational tidal stream turbine.

PubMed

O'Carroll, J P J; Kennedy, R M; Creech, A; Savidge, G

2017-08-01

The effect of modified flow on epifaunal boulder reef communities adjacent to the SeaGen, the world's first grid-compliant tidal stream turbine, were assessed. The wake of the SeaGen was modelled and the outputs were used in conjunction with positional and substrate descriptor variables, to relate variation in epifaunal community structure to the modified physical environment. An Artificial Neural Network (ANN) and Generalised Linear Model (GLM) were used to make predictions on the distribution of Ecological Status (ES) of epifaunal communities in relation to the turbulent wake of the SeaGen. ES was assigned using the High Energy Hard Substrate (HEHS) index. ES was largely High throughout the survey area and it was not possible to make predictions on the spatial distribution of ES using an ANN or GLM. Spatial pattern in epifaunal community structure was detected when the study area was partitioned into three treatment areas: area D1; within one rotor diameter (16 m) of the centre of SeaGen, area D2; between one and three rotor diameters, and area D3; outside of three rotor diameters. Area D1 was found to be significantly more variable than D2 and D3 in terms of epifaunal community structure, bare rock distributions and ES. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two-Dimensional, Ordered, Double Transition Metals Carbides (MXenes)

DOE PAGES

Anasori, Babak; Xie, Yu; Beidaghi, Majid; ...

2015-07-24

The higher the chemical diversity and structural complexity of two-dimensional (2D) materials, the higher the likelihood they possess unique and useful properties. In this paper, density functional theory (DFT) is used to predict the existence of two new families of 2D ordered, carbides (MXenes), M' 2M"C 2 and M' 2M" 2C 3, where M' and M" are two different early transition metals. In these solids, M' layers sandwich M" carbide layers. By synthesizing Mo 2TiC 2T x, Mo 2Ti 2C 3T x, and Cr 2TiC 2T x (where T is a surface termination), we validated the DFT predictions. Since themore » Mo and Cr atoms are on the outside, they control the 2D flakes’ chemical and electrochemical properties. The latter was proven by showing quite different electrochemical behavior of Mo 2TiC 2T x and Ti 3C 2T x. Finally, this work further expands the family of 2D materials, offering additional choices of structures, chemistries, and ultimately useful properties.« less

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

Anasori, Babak; Xie, Yu; Beidaghi, Majid

The higher the chemical diversity and structural complexity of two-dimensional (2D) materials, the higher the likelihood they possess unique and useful properties. In this paper, density functional theory (DFT) is used to predict the existence of two new families of 2D ordered, carbides (MXenes), M' 2M"C 2 and M' 2M" 2C 3, where M' and M" are two different early transition metals. In these solids, M' layers sandwich M" carbide layers. By synthesizing Mo 2TiC 2T x, Mo 2Ti 2C 3T x, and Cr 2TiC 2T x (where T is a surface termination), we validated the DFT predictions. Since themore » Mo and Cr atoms are on the outside, they control the 2D flakes’ chemical and electrochemical properties. The latter was proven by showing quite different electrochemical behavior of Mo 2TiC 2T x and Ti 3C 2T x. Finally, this work further expands the family of 2D materials, offering additional choices of structures, chemistries, and ultimately useful properties.« less

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

USGS Publications Warehouse

Christensen, Nikolaj K; Minsley, Burke J.; Christensen, Steen

2017-01-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

NASA Astrophysics Data System (ADS)

Christensen, N. K.; Minsley, B. J.; Christensen, S.

2017-02-01

We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

The closo-Si{sub 12}C{sub 12} molecule from cluster to crystal: A theoretical prediction

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

Duan, Xiaofeng F., E-mail: xiaofeng.duan@wpafb.af.mil, E-mail: larry.burggraf@us.af.mil; Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio 45433; Burggraf, Larry W., E-mail: xiaofeng.duan@wpafb.af.mil, E-mail: larry.burggraf@us.af.mil

2016-03-21

The structure of closo-Si{sub 12}C{sub 12} is unique among stable Si{sub n}C{sub m} isomers (n, m > 4) because of its high symmetry, π–π stacking of C{sub 6} rings and unsaturated silicon atoms at symmetrical peripheral positions. Dimerization potential surfaces reveal various dimerization reactions that form between two closo-Si{sub 12}C{sub 12} molecules through Si–Si bonds at unsaturated Si atoms. As a result the closo-Si{sub 12}C{sub 12} molecule is capable of polymerization to form stable 1D polymer chains, 2D crystal layers, and 3D crystals. 2D crystal structures formed by side-side polymerization satisfy eight Si valences on each monomer without large distortionmore » of the monomer structure. 3D crystals are formed by stacking 2D structures in the Z direction, preserving registry of C{sub 6} rings in monomer moiety.« less

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor.

PubMed

Malo, Marcus; Persson, Ronnie; Svensson, Peder; Luthman, Kristina; Brive, Lars

2013-03-01

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

(PS)2: protein structure prediction server version 3.0.

PubMed

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Electronic structures and geometries of the XF{sub 3} (X = Cl, Br, I, At) fluorides

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

Sergentu, Dumitru-Claudiu; CEISAM, UMR CNRS 6230, Université de Nantes, 2 Rue de la Houssinière, BP 92208, 44322 Nantes Cedex 3; Amaouch, Mohamed

The potential energy surfaces of the group 17 XF{sub 3} (X = Cl, Br, I, At) fluorides have been investigated for the first time with multiconfigurational wave function theory approaches. In agreement with experiment, bent T-shaped C{sub 2v} structures are computed for ClF{sub 3}, BrF{sub 3}, and IF{sub 3}, while we predict that an average D{sub 3h} structure would be experimentally observed for AtF{sub 3}. Electron correlation and scalar relativistic effects strongly reduce the energy difference between the D{sub 3h} geometry and the C{sub 2v} one, along the XF{sub 3} series, and in the X = At case, spin-orbit couplingmore » also slightly reduces this energy difference. AtF{sub 3} is a borderline system where the D{sub 3h} structure becomes a minimum, i.e., the pseudo-Jahn-Teller effect is inhibited since electron correlation and scalar-relativistic effects create small energy barriers leading to the global C{sub 2v} minima, although both types of effects interfere.« less

Effect of tow alignment on the mechanical performance of 3D woven textile composites

NASA Technical Reports Server (NTRS)

Norman, Timothy L.; Allison, Patti; Baldwin, Jack W.; Gracias, Brian K.; Seesdorf, Dave

1993-01-01

Three-dimensional (3D) woven preforms are currently being considered for use as primary structural components. Lack of technology to properly manufacture, characterize and predict mechanical properties, and predict damage mechanisms leading to failure are problems facing designers of textile composite materials. Two material systems with identical specifications but different manufacturing approaches are investigated. One manufacturing approach resulted in an irregular (nonuniform) preform geometry. The other approach yielded the expected preform geometry (uniform). The objectives are to compare the mechanical properties of the uniform and nonuniform angle interlock 3D weave constructions. The effect of adding layers of laminated tape to the outer surfaces of the textile preform is also examined. Damage mechanisms are investigated and test methods are evaluated.

Recognizing 3 D Objects from 2D Images Using Structural Knowledge Base of Genetic Views

DTIC Science & Technology

1988-08-31

technical report. [BIE85] I. Biederman , "Human image understanding: Recent research and a theory", Computer Vision, Graphics, and Image Processing, vol...model bases", Technical Report 87-85, COINS Dept, University of Massachusetts, Amherst, MA 01003, August 1987 . [BUR87b) Burns, J. B. and L. J. Kitchen...34Recognition in 2D images of 3D objects from large model bases using prediction hierarchies", Proc. IJCAI-10, 1987 . [BUR891 J. B. Burns, forthcoming

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

Mapping Sub-Second Structure in Mouse Behavior

PubMed Central

Wiltschko, Alexander B.; Johnson, Matthew J.; Iurilli, Giuliano; Peterson, Ralph E.; Katon, Jesse M.; Pashkovski, Stan L.; Abraira, Victoria E.; Adams, Ryan P.; Datta, Sandeep Robert

2015-01-01

Summary Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that three-dimensional (3D) mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously-hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior. PMID:26687221

SimRNAweb: a web server for RNA 3D structure modeling with optional restraints.

PubMed

Magnus, Marcin; Boniecki, Michał J; Dawson, Wayne; Bujnicki, Janusz M

2016-07-08

RNA function in many biological processes depends on the formation of three-dimensional (3D) structures. However, RNA structure is difficult to determine experimentally, which has prompted the development of predictive computational methods. Here, we introduce a user-friendly online interface for modeling RNA 3D structures using SimRNA, a method that uses a coarse-grained representation of RNA molecules, utilizes the Monte Carlo method to sample the conformational space, and relies on a statistical potential to describe the interactions in the folding process. SimRNAweb makes SimRNA accessible to users who do not normally use high performance computational facilities or are unfamiliar with using the command line tools. The simplest input consists of an RNA sequence to fold RNA de novo. Alternatively, a user can provide a 3D structure in the PDB format, for instance a preliminary model built with some other technique, to jump-start the modeling close to the expected final outcome. The user can optionally provide secondary structure and distance restraints, and can freeze a part of the starting 3D structure. SimRNAweb can be used to model single RNA sequences and RNA-RNA complexes (up to 52 chains). The webserver is available at http://genesilico.pl/SimRNAweb. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

4f fine-structure levels as the dominant error in the electronic structures of binary lanthanide oxides.

PubMed

Huang, Bolong

2016-04-05

The ground-state 4f fine-structure levels in the intrinsic optical transition gaps between the 2p and 5d orbitals of lanthanide sesquioxides (Ln2 O3 , Ln = La…Lu) were calculated by a two-way crossover search for the U parameters for DFT + U calculations. The original 4f-shell potential perturbation in the linear response method were reformulated within the constraint volume of the given solids. The band structures were also calculated. This method yields nearly constant optical transition gaps between Ln-5d and O-2p orbitals, with magnitudes of 5.3 to 5.5 eV. This result verifies that the error in the band structure calculations for Ln2 O3 is dominated by the inaccuracies in the predicted 4f levels in the 2p-5d transition gaps, which strongly and non-linearly depend on the on-site Hubbard U. The relationship between the 4f occupancies and Hubbard U is non-monotonic and is entirely different from that for materials with 3d or 4d orbitals, such as transition metal oxides. This new linear response DFT + U method can provide a simpler understanding of the electronic structure of Ln2 O3 and enables a quick examination of the electronic structures of lanthanide solids before hybrid functional or GW calculations. © 2015 Wiley Periodicals, Inc.

JET2 Viewer: a database of predicted multiple, possibly overlapping, protein-protein interaction sites for PDB structures.

PubMed

Ripoche, Hugues; Laine, Elodie; Ceres, Nicoletta; Carbone, Alessandra

2017-01-04

The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET 2 at large-scale on more than 20 000 chains. JET 2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET 2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET 2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein-protein interactions modulation and interaction surface redesign. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Motif discovery with data mining in 3D protein structure databases: discovery, validation and prediction of the U-shape zinc binding ("Huf-Zinc") motif.

PubMed

Maurer-Stroh, Sebastian; Gao, He; Han, Hao; Baeten, Lies; Schymkowitz, Joost; Rousseau, Frederic; Zhang, Louxin; Eisenhaber, Frank

2013-02-01

Data mining in protein databases, derivatives from more fundamental protein 3D structure and sequence databases, has considerable unearthed potential for the discovery of sequence motif--structural motif--function relationships as the finding of the U-shape (Huf-Zinc) motif, originally a small student's project, exemplifies. The metal ion zinc is critically involved in universal biological processes, ranging from protein-DNA complexes and transcription regulation to enzymatic catalysis and metabolic pathways. Proteins have evolved a series of motifs to specifically recognize and bind zinc ions. Many of these, so called zinc fingers, are structurally independent globular domains with discontinuous binding motifs made up of residues mostly far apart in sequence. Through a systematic approach starting from the BRIX structure fragment database, we discovered that there exists another predictable subset of zinc-binding motifs that not only have a conserved continuous sequence pattern but also share a characteristic local conformation, despite being included in totally different overall folds. While this does not allow general prediction of all Zn binding motifs, a HMM-based web server, Huf-Zinc, is available for prediction of these novel, as well as conventional, zinc finger motifs in protein sequences. The Huf-Zinc webserver can be freely accessed through this URL (http://mendel.bii.a-star.edu.sg/METHODS/hufzinc/).

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

Predicting RNA 3D structure using a coarse-grain helix-centered model

PubMed Central

Kerpedjiev, Peter; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

2015-01-01

A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. PMID:25904133

Dispersion corrected hartree-fock and density functional theory for organic crystal structure prediction.

PubMed

Brandenburg, Jan Gerit; Grimme, Stefan

2014-01-01

We present and evaluate dispersion corrected Hartree-Fock (HF) and Density Functional Theory (DFT) based quantum chemical methods for organic crystal structure prediction. The necessity of correcting for missing long-range electron correlation, also known as van der Waals (vdW) interaction, is pointed out and some methodological issues such as inclusion of three-body dispersion terms are discussed. One of the most efficient and widely used methods is the semi-classical dispersion correction D3. Its applicability for the calculation of sublimation energies is investigated for the benchmark set X23 consisting of 23 small organic crystals. For PBE-D3 the mean absolute deviation (MAD) is below the estimated experimental uncertainty of 1.3 kcal/mol. For two larger π-systems, the equilibrium crystal geometry is investigated and very good agreement with experimental data is found. Since these calculations are carried out with huge plane-wave basis sets they are rather time consuming and routinely applicable only to systems with less than about 200 atoms in the unit cell. Aiming at crystal structure prediction, which involves screening of many structures, a pre-sorting with faster methods is mandatory. Small, atom-centered basis sets can speed up the computation significantly but they suffer greatly from basis set errors. We present the recently developed geometrical counterpoise correction gCP. It is a fast semi-empirical method which corrects for most of the inter- and intramolecular basis set superposition error. For HF calculations with nearly minimal basis sets, we additionally correct for short-range basis incompleteness. We combine all three terms in the HF-3c denoted scheme which performs very well for the X23 sublimation energies with an MAD of only 1.5 kcal/mol, which is close to the huge basis set DFT-D3 result.

Protein modeling and molecular dynamics simulation of SlWRKY4 protein cloned from drought tolerant tomato (Solanum habrochaites) line EC520061.

PubMed

Karkute, Suhas G; Easwaran, Murugesh; Gujjar, Ranjit Singh; Piramanayagam, Shanmughavel; Singh, Major

2015-10-01

WRKY genes are members of one of the largest families of plant transcription factors and play an important role in response to biotic and abiotic stresses, and overall growth and development. Understanding the interaction of WRKY proteins with other proteins/ligands in plant cells is of utmost importance to develop plants having tolerance to biotic and abiotic stresses. The SlWRKY4 gene was cloned from a drought tolerant wild species of tomato (Solanum habrochaites) and the secondary structure and 3D modeling of this protein were predicted using Schrödinger Suite-Prime. Predicted structures were also subjected to plot against Ramachandran's conformation, and the modeled structure was minimized using Macromodel. Finally, the minimized structure was simulated in the water environment to check the protein stability. The behavior of the modeled structure was well-simulated and analyzed through RMSD and RMSF of the protein. The present work provides the modeled 3D structure of SlWRKY4 that will help in understanding the mechanism of gene regulation by further in silico interaction studies.

Palladium(II) complexes bearing di-(2-picolyl)amine functionalized chrysin fragments. An experimental and theoretical study

NASA Astrophysics Data System (ADS)

González-Montiel, Simplicio; Valdez-Calderón, Alejandro; Vásquez-Pérez, J. Manuel; Torres-Valencia, J. Martín; Martínez-Otero, Diego; López, Jorge A.; Cruz-Borbolla, Julián

2017-10-01

A new series of chrysin derivatives containing the di-(2-picolyl)amine (2a-d) moiety have been designed, synthesized, and treated with PdCl2·2CH3CN allowing the preparation of new cationic Palladium(II) complexes (3a-d). Solution-phase studies by 1H NMR spectroscopy of 3a-d revealed that the protons of the methylene groups of the di(2-picolyl)amine fragment are diasterotopic. GIAO/DFT studies were performed to predict the molecular structures of 3a-d by comparing the experimental and theoretical 1H-NMR chemical shifts. The molecular structure of 3c was determined by X-ray crystallographic analysis revealing that di-(2-picolyl)amine fragment is coordinated to the palladium center in a κ3-N,N,N-tridentate fashion in an overall square-planar geometry completed with a chloride atom.

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium.

PubMed

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein.

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium

PubMed Central

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein. PMID:23275704

An exo-β-(1→3)-D-galactanase from Streptomyces sp. provides insights into type II arabinogalactan structure

PubMed Central

Ling, Naomi X.-Y.; Lee, Joanne; Ellis, Miriam; Liao, Ming-Long; Mau, Shaio-Lim; Guest, David; Janssen, Peter H.; Kováč, Pavol; Bacic, Antony; Pettolino, Filomena A.

2012-01-01

An exo-β-(1→3)-D-galactanase (SGalase1) that specifically cleaves the β-(1→3)-D-galactan backbone of arabinogalactan-proteins (AGPs) was isolated from culture filtrates of a soil Streptomyces sp. Internal peptide sequence information was used to clone and recombinantly express the gene in E. coli. The molecular mass of the isolated enzyme was ~45 kDa, similar to the 48.2 kDa mass predicted from the amino acid sequence. The pI, pH and temperature optima for the enzyme were ~7.45, 3.8 and 48 °C, respectively. The native and recombinant enzymes specifically hydrolysed β-(1→3)-D-galacto-oligo- or poly-saccharides from the upstream (non-reducing) end, typical of an exo-acting enzyme. A second homologous Streptomyces gene (SGalase2) was also cloned and expressed. SGalase2 was similar in size (47.9 kDa) and enzyme activity to SGalase1 but differed in its pH optimum (pH 5). Both SGalase1 and SGalase2 are predicted to belong to the CAZy glycosyl hydrolase family GH 43 based on activity, sequence homology and phylogenetic analysis. The Km and Vmax of the native exo-β-(1→3)-D-galactanase for de-arabinosylated gum arabic (dGA) were 19 mg/ml and 9.7 μmol D-Gal/min/mg protein, respectively. The activity of these enzymes is well suited for the study of type II galactan structures and provides an important tool for the investigation of the biological role of AGPs in plants. De-arabinosylated gum arabic (dGA) was used as a model to investigate the use of these enzymes in defining type II galactan structure. Exhaustive hydrolysis of dGA resulted in a limited number of oligosaccharide products with a trisaccharide of Gal2GlcA1 predominating. PMID:22464224

Electronic structure of the chiral helimagnet and 3d-intercalated transition metal dichalcogenide Cr 1/3NbS 2

DOE PAGES

Sirca, N.; Mo, S. -K.; Bondino, F.; ...

2016-08-18

The electronic structure of the chiral helimagnet Cr 1/3NbS 2 has been studied with core level and angle-resolved photoemission spectroscopy (ARPES). Intercalated Cr atoms are found to be effective in donating electrons to the NbS 2 layers but also cause significant modifications of the electronic structure of the host NbS 2 material. Specifically, the data provide evidence that a description of the electronic structure of Cr 1/3NbS 2 on the basis of a simple rigid band picture is untenable. The data also reveal substantial inconsistencies with the predictions of standard density functional theory. In conclusion, the relevance of these resultsmore » to the attainment of a correct description of the electronic structure of chiral helimagnets, magnetic thin films/multilayers, and transition metal dichalcogenides intercalated with 3d magnetic elements is discussed.« less

Prelude and Fugue, predicting local protein structure, early folding regions and structural weaknesses.

PubMed

Kwasigroch, Jean Marc; Rooman, Marianne

2006-07-15

Prelude&Fugue are bioinformatics tools aiming at predicting the local 3D structure of a protein from its amino acid sequence in terms of seven backbone torsion angle domains, using database-derived potentials. Prelude(&Fugue) computes all lowest free energy conformations of a protein or protein region, ranked by increasing energy, and possibly satisfying some interresidue distance constraints specified by the user. (Prelude&)Fugue detects sequence regions whose predicted structure is significantly preferred relative to other conformations in the absence of tertiary interactions. These programs can be used for predicting secondary structure, tertiary structure of short peptides, flickering early folding sequences and peptides that adopt a preferred conformation in solution. They can also be used for detecting structural weaknesses, i.e. sequence regions that are not optimal with respect to the tertiary fold. http://babylone.ulb.ac.be/Prelude_and_Fugue.

Computational identification of promising thermoelectric materials among known quasi-2D binary compounds

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

Gorai, Prashun; Toberer, Eric S.; Stevanović, Vladan

Quasi low-dimensional structures are abundant among known thermoelectric materials, primarily because of their low lattice thermal conductivities. In this work, we have computationally assessed the potential of 427 known binary quasi-2D structures in 272 different chemistries for thermoelectric performance. To assess the thermoelectric performance, we employ an improved version of our previously developed descriptor for thermoelectric performance [Yan et al., Energy Environ. Sci., 2015, 8, 983]. The improvement is in the explicit treatment of van der Waals interactions in quasi-2D materials, which leads to significantly better predictions of their crystal structures and lattice thermal conductivities. The improved methodology correctly identifiesmore » known binary quasi-2D thermoelectric materials such as Sb2Te3, Bi2Te3, SnSe, SnS, InSe, and In2Se3. As a result, we propose candidate quasi-2D binary materials, a number of which have not been previously considered for thermoelectric applications.« less

Structure of the Kπ = 4+ bands in 186,188Os

NASA Astrophysics Data System (ADS)

Phillips, A. A.; Garrett, P. E.; Bettermann, L.; Braun, N.; Burke, D. G.; Demand, G. A.; Faestermann, T.; Finlay, P.; Green, K. L.; Hertenberger, R.; Krü; cken, R.; Leach, K. G.; Schumaker, M. A.; Svensson, C. E.; Wirth, H.-F.; Wong, J.

2009-01-01

The structures of 3+ states in Os have been debated over several decades. Based on measured B(E2) values they were interpreted in 186-192Os as Kπ = 4+ two-phonon vibrations, whereas inelastic scattering, and (t,α) work imply a hexadecapole phonon description. To clarify the nature of these Kπ = 4+ bands in 186,188Os, we performed a (3He,d) reaction on 185,187Re targets using 30 MeV 3He beams and a Q3D spectrograph. Absolute cross sections were obtained for excited states up to 3 MeV at 9 angles from 5° to 50°. Results indicate a significant 5/2+[402]π+3/2+[402]π component in agreement with quasiparticle phonon model predictions for a single hexadecapole phonon structure.

Multi-shape active composites by 3D printing of digital shape memory polymers

NASA Astrophysics Data System (ADS)

Wu, Jiangtao; Yuan, Chao; Ding, Zhen; Isakov, Michael; Mao, Yiqi; Wang, Tiejun; Dunn, Martin L.; Qi, H. Jerry

2016-04-01

Recent research using 3D printing to create active structures has added an exciting new dimension to 3D printing technology. After being printed, these active, often composite, materials can change their shape over time; this has been termed as 4D printing. In this paper, we demonstrate the design and manufacture of active composites that can take multiple shapes, depending on the environmental temperature. This is achieved by 3D printing layered composite structures with multiple families of shape memory polymer (SMP) fibers - digital SMPs - with different glass transition temperatures (Tg) to control the transformation of the structure. After a simple single-step thermomechanical programming process, the fiber families can be sequentially activated to bend when the temperature is increased. By tuning the volume fraction of the fibers, bending deformation can be controlled. We develop a theoretical model to predict the deformation behavior for better understanding the phenomena and aiding the design. We also design and print several flat 2D structures that can be programmed to fold and open themselves when subjected to heat. With the advantages of an easy fabrication process and the controllable multi-shape memory effect, the printed SMP composites have a great potential in 4D printing applications.

Multi-shape active composites by 3D printing of digital shape memory polymers.

PubMed

Wu, Jiangtao; Yuan, Chao; Ding, Zhen; Isakov, Michael; Mao, Yiqi; Wang, Tiejun; Dunn, Martin L; Qi, H Jerry

2016-04-13

Recent research using 3D printing to create active structures has added an exciting new dimension to 3D printing technology. After being printed, these active, often composite, materials can change their shape over time; this has been termed as 4D printing. In this paper, we demonstrate the design and manufacture of active composites that can take multiple shapes, depending on the environmental temperature. This is achieved by 3D printing layered composite structures with multiple families of shape memory polymer (SMP) fibers - digital SMPs - with different glass transition temperatures (Tg) to control the transformation of the structure. After a simple single-step thermomechanical programming process, the fiber families can be sequentially activated to bend when the temperature is increased. By tuning the volume fraction of the fibers, bending deformation can be controlled. We develop a theoretical model to predict the deformation behavior for better understanding the phenomena and aiding the design. We also design and print several flat 2D structures that can be programmed to fold and open themselves when subjected to heat. With the advantages of an easy fabrication process and the controllable multi-shape memory effect, the printed SMP composites have a great potential in 4D printing applications.

Multi-shape active composites by 3D printing of digital shape memory polymers

PubMed Central

Wu, Jiangtao; Yuan, Chao; Ding, Zhen; Isakov, Michael; Mao, Yiqi; Wang, Tiejun; Dunn, Martin L.; Qi, H. Jerry

2016-01-01

Recent research using 3D printing to create active structures has added an exciting new dimension to 3D printing technology. After being printed, these active, often composite, materials can change their shape over time; this has been termed as 4D printing. In this paper, we demonstrate the design and manufacture of active composites that can take multiple shapes, depending on the environmental temperature. This is achieved by 3D printing layered composite structures with multiple families of shape memory polymer (SMP) fibers – digital SMPs - with different glass transition temperatures (Tg) to control the transformation of the structure. After a simple single-step thermomechanical programming process, the fiber families can be sequentially activated to bend when the temperature is increased. By tuning the volume fraction of the fibers, bending deformation can be controlled. We develop a theoretical model to predict the deformation behavior for better understanding the phenomena and aiding the design. We also design and print several flat 2D structures that can be programmed to fold and open themselves when subjected to heat. With the advantages of an easy fabrication process and the controllable multi-shape memory effect, the printed SMP composites have a great potential in 4D printing applications. PMID:27071543

Evaluation of microvascular anastomosis using real-time ultrahigh resolution Fourier domain Doppler optical coherence tomography

PubMed Central

Huang, Yong; Tong, Dedi; Zhu, Shan; Wu, Lehao; Mao, Qi; Ibrahim, Zuhaib; Lee, WP Andrew; Brandacher, Gerald; Kang, Jin U.

2014-01-01

Background Evolution and improvements in microsurgical techniques and tools have paved the way for super-microsurgical anastomoses with vessel diameters often approaching below 0.8 mm in the clinical realm and even smaller (0.2–0.3 mm) in murine models. Several imaging and monitoring devices have been introduced for post-operative monitoring but intra-operative guidance, assessment and predictability have remained limited to binocular optical microscope and surgeon’s experience. We present a high-resolution real time 3D imaging modality for intra-operative evaluation of luminal narrowing, thrombus formation and flow alterations. Methods An imaging modality that provides immediate, in-depth high resolution 3D structure view and flow information of the anastomosed site called phase resolved Doppler optical coherence tomography (PRDOCT) was developed. 22 mouse femoral artery anastomoses and 17 mouse venous anastomoses were performed and evaluated with PRDOCT. Flow status, vessel inner lumen 3D structure, and early thrombus detection were analyzed based on PRDOCT imaging results. Initial PRDOCT based predictions were correlated with actual long term surgical outcomes. Eventually four cases of mouse orthotopic limb transplantation were carried out and PRDOCT predicted long term patency were confirmed by actual results. Results PRDOCT was able to provide high-resolution 3D visualization of the vessel flow status and vessel inner lumen. The assessments based on PRDOCT visualization shows a 92% sensitivity and 90% specificity for arterial anastomoses and 90% sensitivity and 86% specificity for venous anastomoses. Conclusions PRDOCT is an effective evaluation tool for microvascular anastomosis. It can predict the long term vessel patency with high sensitivity and specificity. PMID:25811583

Three-Dimensional Sensitivity Kernels of Z/H Amplitude Ratios of Surface and Body Waves

NASA Astrophysics Data System (ADS)

Bao, X.; Shen, Y.

2017-12-01

The ellipticity of Rayleigh wave particle motion, or Z/H amplitude ratio, has received increasing attention in inversion for shallow Earth structures. Previous studies of the Z/H ratio assumed one-dimensional (1D) velocity structures beneath the receiver, ignoring the effects of three-dimensional (3D) heterogeneities on wave amplitudes. This simplification may introduce bias in the resulting models. Here we present 3D sensitivity kernels of the Z/H ratio to Vs, Vp, and density perturbations, based on finite-difference modeling of wave propagation in 3D structures and the scattering-integral method. Our full-wave approach overcomes two main issues in previous studies of Rayleigh wave ellipticity: (1) the finite-frequency effects of wave propagation in 3D Earth structures, and (2) isolation of the fundamental mode Rayleigh waves from Rayleigh wave overtones and converted Love waves. In contrast to the 1D depth sensitivity kernels in previous studies, our 3D sensitivity kernels exhibit patterns that vary with azimuths and distances to the receiver. The laterally-summed 3D sensitivity kernels and 1D depth sensitivity kernels, based on the same homogeneous reference model, are nearly identical with small differences that are attributable to the single period of the 1D kernels and a finite period range of the 3D kernels. We further verify the 3D sensitivity kernels by comparing the predictions from the kernels with the measurements from numerical simulations of wave propagation for models with various small-scale perturbations. We also calculate and verify the amplitude kernels for P waves. This study shows that both Rayleigh and body wave Z/H ratios provide vertical and lateral constraints on the structure near the receiver. With seismic arrays, the 3D kernels afford a powerful tool to use the Z/H ratios to obtain accurate and high-resolution Earth models.

Fundamentals, progress, and future directions of nitride-based semiconductors and their composites in two-dimensional limit: A first-principles perspective to recent synthesis

NASA Astrophysics Data System (ADS)

Kecik, D.; Onen, A.; Konuk, M.; Gürbüz, E.; Ersan, F.; Cahangirov, S.; Aktürk, E.; Durgun, E.; Ciraci, S.

2018-03-01

Potential applications of bulk GaN and AlN crystals have made possible single and multilayer allotropes of these III-V compounds to be a focus of interest recently. As of 2005, the theoretical studies have predicted that GaN and AlN can form two-dimensional (2D) stable, single-layer (SL) structures being wide band gap semiconductors and showing electronic and optical properties different from those of their bulk parents. Research on these 2D structures have gained importance with recent experimental studies achieving the growth of ultrathin 2D GaN and AlN on substrates. It is expected that these two materials will open an active field of research like graphene, silicene, and transition metal dichalcogenides. This topical review aims at the evaluation of previous experimental and theoretical works until 2018 in order to provide input for further research attempts in this field. To this end, starting from three-dimensional (3D) GaN and AlN crystals, we review 2D SL and multilayer (ML) structures, which were predicted to be stable in free-standing states. These are planar hexagonal (or honeycomb), tetragonal, and square-octagon structures. First, we discuss earlier results on dynamical and thermal stability of these SL structures, as well as the predicted mechanical properties. Next, their electronic and optical properties with and without the effect of strain are reviewed and compared with those of the 3D parent crystals. The formation of multilayers, hence prediction of new periodic layered structures and also tuning their physical properties with the number of layers are other critical subjects that have been actively studied and discussed here. In particular, an extensive analysis pertaining to the nature of perpendicular interlayer bonds causing planar GaN and AlN to buckle is presented. In view of the fact that SL GaN and AlN can be fabricated only on a substrate, the question of how the properties of free-standing, SL structures are affected if they are grown on a substrate is addressed. We also examine recent works treating the composite structures of GaN and AlN joined commensurately along their zigzag and armchair edges and forming heterostructures, δ-doping, single, and multiple quantum wells, as well as core/shell structures. Finally, outlooks and possible new research directions are briefly discussed.

Bioactive constituents of oleanane-type triterpene saponins from the roots of Glycyrrhiza glabra.

PubMed

Wei, Juan-Hua; Zheng, Yun-Feng; Li, Cun-Yu; Tang, Yu-Ping; Peng, Guo-Ping

2014-01-01

Three new oleanane-type triterpene saponins, namely licorice-saponin M3 (1), licorice-saponin N4 (2), and licorice-saponin O4 (3), an artificial product (4), as well as five known triterpene glucuronides (5-9), were isolated from the roots of Glycyrrhiza glabra L. Their structures were established using 1D and 2D NMR spectroscopy, mass spectrometry, and by comparison with spectroscopic data reported in the literature. The inhibitory effects of the selected compounds on neuraminidase were evaluated, and the preliminary structure-activity relationship was also predicted.

Electronic band structures and excitonic properties of delafossites: A GW-BSE study

NASA Astrophysics Data System (ADS)

Wang, Xiaoming; Meng, Weiwei; Yan, Yanfa

2017-08-01

We report the band structures and excitonic properties of delafossites CuMO2 (M=Al, Ga, In, Sc, Y, Cr) calculated using the state-of-the-art GW-BSE approach. We evaluate different levels of self-consistency of the GW approximations, namely G0W0, GW0, GW, and QSGW, on the band structures and find that GW0, in general, predicts the band gaps in better agreement with experiments considering the electron-hole effect. For CuCrO2, the HSE wave function is used as the starting point for the perturbative GW0 calculations, since it corrects the band orders wrongly predicted by PBE. The discrepancy about the valence band characters of CuCrO2 is classified based on both HSE and QSGW calculations. The PBE wave functions, already good, are used for other delafossites. All the delafossites are shown to be indirect band gap semiconductors with large exciton binding energies, varying from 0.24 to 0.44 eV, in consistent with experimental findings. The excitation mechanisms are explained by examining the exciton amplitude projections on the band structures. Discrepancies compared with experiments are also addressed. The lowest and strongest exciton, mainly contributed from either Cu 3d → Cu 3p (Al, Ga, In) or Cu 3d → M 3d (M = Sc, Y, Cr) transitions, is always located at the L point of the rhombohedral Brillouin zone.

Docking and 3-D QSAR studies on indolyl aryl sulfones. Binding mode exploration at the HIV-1 reverse transcriptase non-nucleoside binding site and design of highly active N-(2-hydroxyethyl)carboxamide and N-(2-hydroxyethyl)carbohydrazide derivatives.

PubMed

Ragno, Rino; Artico, Marino; De Martino, Gabriella; La Regina, Giuseppe; Coluccia, Antonio; Di Pasquali, Alessandra; Silvestri, Romano

2005-01-13

Three-dimensional quantitative structure-activity relationship (3-D QSAR) studies and docking simulations were developed on indolyl aryl sulfones (IASs), a class of novel HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (Silvestri, et al. J. Med. Chem. 2003, 46, 2482-2493) highly active against wild type and some clinically relevant resistant strains (Y181C, the double mutant K103N-Y181C, and the K103R-V179D-P225H strain, highly resistant to efavirenz). Predictive 3-D QSAR models using the combination of GRID and GOLPE programs were obtained using a receptor-based alignment by means of docking IASs into the non-nucleoside binding site (NNBS) of RT. The derived 3-D QSAR models showed conventional correlation (r(2)) and cross-validated (q(2)) coefficients values ranging from 0.79 to 0.93 and from 0.59 to 0.84, respectively. All described models were validated by an external test set compiled from previously reported pyrryl aryl sulfones (Artico, et al. J. Med. Chem. 1996, 39, 522-530). The most predictive 3-D QSAR model was then used to predict the activity of novel untested IASs. The synthesis of six designed derivatives (prediction set) allowed disclosure of new IASs endowed with high anti-HIV-1 activities.

Enhanced multimaterial 4D printing with active hinges

NASA Astrophysics Data System (ADS)

Akbari, Saeed; Hosein Sakhaei, Amir; Kowsari, Kavin; Yang, Bill; Serjouei, Ahmad; Yuanfang, Zhang; Ge, Qi

2018-06-01

Despite great progress in four-dimensional (4D) printing, i.e. three-dimensional (3D) printing of active (stimuli-responsive) materials, the relatively low actuation force of the 4D printed structures often impedes their engineering applications. In this study, we use multimaterial inkjet 3D printing technology to fabricate shape memory structures, including a morphing wing flap and a deployable structure, which consist of active and flexible hinges joining rigid (non-active) parts. The active hinges, printed from a shape memory polymer (SMP), lock the structure into a second temporary shape during a thermomechanical programming process, while the flexible hinges, printed from an elastomer, effectively increase the actuation force and the load-bearing capacity of the printed structure as reflected in the recovery ratio. A broad range of mechanical properties such as modulus and failure strain can be achieved for both active and flexible hinges by varying the composition of the two base materials, i.e. the SMP and the elastomer, to accommodate large deformation induced during programming step, and enhance the recovery in the actuating step. To find the important design parameters, including local deformation, shape fixity and recovery ratio, we conduct high fidelity finite element simulations, which are able to accurately predict the nonlinear deformation of the printed structures. In addition, a coupled thermal-electrical finite element analysis was performed to model the heat transfer within the active hinges during the localized Joule heating process. The model predictions showed good agreement with the measured temperature data and were used to find the major parameters affecting temperature distribution including the applied voltage and the convection rate.

Finding Furfural Hydrogenation Catalysts via Predictive Modelling

PubMed Central

Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

2010-01-01

Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

The "universal" behavior of the Breakthrough Curve in 3D aquifer transport and the validity of the First-Order solution

NASA Astrophysics Data System (ADS)

Jankovic, Igor; Maghrebi, Mahdi; Fiori, Aldo; Zarlenga, Antonio; Dagan, Gedeon

2017-04-01

We examine the impact of permeability structures on the Breakthrough Curve (BTC) of solute, at a distance x from the injection plane, under mean uniform flow of mean velocity U. The study is carried out through accurate 3D numerical simulations, rather than the 2D models adopted in most of previous works. All structures share the same univariate distribution of the logconductivity Y = lnK and autocorrelation function ρY , but differ in higher order statistics. The main finding is that the BTC of ergodic plumes for the different examined structures is quite robust, displaying a seemingly "universal" behavior. The result is in variance with similar analyses carried out in the past for 2D permeability structures. The basic parameters (i.e. the geometric mean, the logconductivity variance σY 2 and the horizontal integral scale I) have to be identified from field data (e.g. core analysis, pumping test or other methods). However, prediction requires the knowledge of U, and the results suggest that improvement of the BTC prediction in applications can be achieved by independent estimates of the mean velocity U, e.g. by pumping tests, rather than attempting to characterize the permeability structure beyond its second-order characterization. The BTC prediction made by the Inverse Gaussian (IG) distribution, adopting the macrodispersion coefficient estimated by the First Order approximation αL = σY 2I, is also quite robust, providing a simple and effective solution to be employed in applications. The consequences of the latter result are further explored by modeling the mass distribution that occurred at the MADE-1 natural gradient experiment, for which we show that most of the plume features are adequately captured by the simple First Order approach.

Use of integrated analogue and numerical modelling to predict tridimensional fracture intensity in fault-related-folds.

NASA Astrophysics Data System (ADS)

Pizzati, Mattia; Cavozzi, Cristian; Magistroni, Corrado; Storti, Fabrizio

2016-04-01

Fracture density pattern predictions with low uncertainty is a fundamental issue for constraining fluid flow pathways in thrust-related anticlines in the frontal parts of thrust-and-fold belts and accretionary prisms, which can also provide plays for hydrocarbon exploration and development. Among the drivers that concur to determine the distribution of fractures in fold-and-thrust-belts, the complex kinematic pathways of folded structures play a key role. In areas with scarce and not reliable underground information, analogue modelling can provide effective support for developing and validating reliable hypotheses on structural architectures and their evolution. In this contribution, we propose a working method that combines analogue and numerical modelling. We deformed a sand-silicone multilayer to eventually produce a non-cylindrical thrust-related anticline at the wedge toe, which was our test geological structure at the reservoir scale. We cut 60 serial cross-sections through the central part of the deformed model to analyze faults and folds geometry using dedicated software (3D Move). The cross-sections were also used to reconstruct the 3D geometry of reference surfaces that compose the mechanical stratigraphy thanks to the use of the software GoCad. From the 3D model of the experimental anticline, by using 3D Move it was possible to calculate the cumulative stress and strain underwent by the deformed reference layers at the end of the deformation and also in incremental steps of fold growth. Based on these model outputs it was also possible to predict the orientation of three main fractures sets (joints and conjugate shear fractures) and their occurrence and density on model surfaces. The next step was the upscaling of the fracture network to the entire digital model volume, to create DFNs.

D2N: Distance to the native.

PubMed

Mishra, Avinash; Rana, Prashant Singh; Mittal, Aditya; Jayaram, B

2014-10-01

Root-mean-square-deviation (RMSD), of computationally-derived protein structures from experimentally determined structures, is a critical index to assessing protein-structure-prediction-algorithms (PSPAs). The development of PSPAs to obtain 0Å RMSD from native structures is considered central to computational biology. However, till date it has been quite challenging to measure how far a predicted protein structure is from its native - in the absence of a known experimental/native structure. In this work, we report the development of a metric "D2N" (distance to the native) - that predicts the "RMSD" of any structure without actually knowing the native structure. By combining physico-chemical properties and known universalities in spatial organization of soluble proteins to develop D2N, we demonstrate the ability to predict the distance of a proposed structure to within ±1.5Ǻ error with a remarkable average accuracy of 93.6% for structures below 5Ǻ from the native. We believe that this work opens up a completely new avenue towards assigning reliable structures to whole proteomes even in the absence of experimentally determined native structures. The D2N tool is freely available at http://www.scfbio-iitd.res.in/software/d2n.jsp. Copyright © 2014 Elsevier B.V. All rights reserved.

Geometric modeling of Plateau borders using the orthographic projection method for closed cell rigid polyurethane foam thermal conductivity prediction

NASA Astrophysics Data System (ADS)

Xu, Jie; Wu, Tao; Peng, Chuang; Adegbite, Stephen

2017-09-01

The geometric Plateau border model for closed cell polyurethane foam was developed based on volume integrations of approximated 3D four-cusp hypocycloid structure. The tetrahedral structure of convex struts was orthogonally projected into 2D three-cusp deltoid with three central cylinders. The idealized single unit strut was modeled by superposition. The volume of each component was calculated by geometric analyses. The strut solid fraction f s and foam porosity coefficient δ were calculated based on representative elementary volume of Kelvin and Weaire-Phelan structures. The specific surface area Sv derived respectively from packing structures and deltoid approximation model were put into contrast against strut dimensional ratio ɛ. The characteristic foam parameters obtained from this semi-empirical model were further employed to predict foam thermal conductivity.

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

DOE PAGES

Slater, Anna G.; Reiss, Paul S.; Pulido, Angeles; ...

2017-06-20

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal-organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groupsmore » into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure-energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy-structure-function maps.« less

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

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

Slater, Anna G.; Reiss, Paul S.; Pulido, Angeles

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal-organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groupsmore » into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure-energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy-structure-function maps.« less

Exploration of tetrahedral structures in silicate cathodes using a motif-network scheme

PubMed Central

Zhao, Xin; Wu, Shunqing; Lv, Xiaobao; Nguyen, Manh Cuong; Wang, Cai-Zhuang; Lin, Zijing; Zhu, Zi-Zhong; Ho, Kai-Ming

2015-01-01

Using a motif-network search scheme, we studied the tetrahedral structures of the dilithium/disodium transition metal orthosilicates A2MSiO4 with A = Li or Na and M = Mn, Fe or Co. In addition to finding all previously reported structures, we discovered many other different tetrahedral-network-based crystal structures which are highly degenerate in energy. These structures can be classified into structures with 1D, 2D and 3D M-Si-O frameworks. A clear trend of the structural preference in different systems was revealed and possible indicators that affect the structure stabilities were introduced. For the case of Na systems which have been much less investigated in the literature relative to the Li systems, we predicted their ground state structures and found evidence for the existence of new structural motifs. PMID:26497381

Prediction and synthesis of a family of atomic laminate phases with Kagomé-like and in-plane chemical ordering

PubMed Central

Dahlqvist, Martin; Lu, Jun; Meshkian, Rahele; Tao, Quanzheng; Hultman, Lars; Rosen, Johanna

2017-01-01

The enigma of MAX phases and their hybrids prevails. We probe transition metal (M) alloying in MAX phases for metal size, electronegativity, and electron configuration, and discover ordering in these MAX hybrids, namely, (V2/3Zr1/3)2AlC and (Mo2/3Y1/3)2AlC. Predictive theory and verifying materials synthesis, including a judicious choice of alloying M from groups III to VI and periods 4 and 5, indicate a potentially large family of thermodynamically stable phases, with Kagomé-like and in-plane chemical ordering, and with incorporation of elements previously not known for MAX phases, including the common Y. We propose the structure to be monoclinic C2/c. As an extension of the work, we suggest a matching set of novel MXenes, from selective etching of the A-element. The demonstrated structural design on simultaneous two-dimensional (2D) and 3D atomic levels expands the property tuning potential of functional materials. PMID:28776034

Structural stability and mechanical properties of technetium mononitride (TcN)

NASA Astrophysics Data System (ADS)

Soni, Shubhangi; Choudhary, K. K.; Kaurav, Netram

2018-05-01

Among the nitrides, 3d and 4d transition metal nitrides have been investigated both experimentally and theoretically due to their predominant performances and enormous applications. In the present paper, we have attempted to predict the structural stability and mechanical properties of technetium mononitride (TcN) using an effective interionic interaction potential, which includes the long range Coulomb, van der Waals (vdW) interaction and the short-range repulsive interaction upto second-neighbor ions within the Hafemeister and Flygare approach. Our theoretical approach reveals the structural phase transition of the TcN B3 to B1 structure, wherein, the Gibbs' free energies of both the structures were minimized. The variations of elastic constants with pressure follow a systematic trend identical to that observed in other compounds of ZnS type structure family.

Synthesis, Spectra, and Theoretical Investigations of 1,3,5-Triazines Compounds as Ultraviolet Rays Absorber Based on Time-Dependent Density Functional Calculations and three-Dimensional Quantitative Structure-Property Relationship.

PubMed

Wang, Xueding; Xu, Yilian; Yang, Lu; Lu, Xiang; Zou, Hao; Yang, Weiqing; Zhang, Yuanyuan; Li, Zicheng; Ma, Menglin

2018-03-01

A series of 1,3,5-triazines were synthesized and their UV absorption properties were tested. The computational chemistry methods were used to construct quantitative structure-property relationship (QSPR), which was used to computer aided design of new 1,3,5-triazines ultraviolet rays absorber compounds. The experimental UV absorption data are in good agreement with those predicted data using the Time-dependent density functional theory (TD-DFT) [B3LYP/6-311 + G(d,p)]. A suitable forecasting model (R > 0.8, P < 0.0001) was revealed. Predictive three-dimensional quantitative structure-property relationship (3D-QSPR) model was established using multifit molecular alignment rule of Sybyl program, which conclusion is consistent with the TD-DFT calculation. The exceptional photostability mechanism of such ultraviolet rays absorber compounds was studied and confirmed as principally banked upon their ability to undergo excited-state deactivation via an ultrafast excited-state proton transfer (ESIPT). The intramolecular hydrogen bond (IMHB) of 1,3,5-triazines compounds is the basis for the excited state proton transfer, which was explored by IR spectroscopy, UV spectra, structural and energetic aspects of different conformers and frontier molecular orbitals analysis.

Structure and reactivity studies of CoHNO{sup +} in the gas phase

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

Chen, H.; Jacobson, D.B.; Freiser, B.S.

1999-12-16

The structure and energetics of three CoHNO{sup +} isomers [HCo(NO){sup +} (1), Co(HNO){sup +} (2), Co(NOH){sup +} (3)] were probed by using density functional theory (DFT). Theory predicts that 2 is the most stable structure with 1 and 3 14.1 and 15.4 kcal/mol less stable. The transition states for 2 {yields} 1 and 2 {yields} 3 conversions were not located. DFT calculations predict D{degree}(CoH{sup +}-NO) = 34.6 kcal/mol and D{degree}(Co{sup +}-HNO) = 45.5 kcal/mol. The gas-phase ion chemistry of CoHNO{sup +} was also studied by using Fourier transform ion cyclotron resonance (FTICR) mass spectrometry. CID and SORI-CID of CoHNO{sup +}more » yield competitive formation of Co{sup +}, CoH{sup +}, and CoNO{sup +}. These results suggest that the barrier for 2 {yields} 1 conversion is less than 45.5 kcal/mol. Reactions with simple molecules were dominated by NO and HNO displacements. Potential energy surface diagrams are presented to explain these displacement reactions. Surprisingly, CoHNO{sup +} reacts with methane by dehydrogenation to yield CoCH{sub 3}NO{sup +}. Studies suggest CH{sub 3}CoNO{sup +} rather than Co(CH{sub 3}NO){sup +}as the structure for this ion.« less

Li2 B12 and Li3 B12 : Prediction of the Smallest Tubular and Cage-like Boron Structures.

PubMed

Dong, Xue; Jalife, Said; Vásquez-Espinal, Alejandro; Ravell, Estefanía; Pan, Sudip; Cabellos, José Luis; Liang, Wei-Yan; Cui, Zhong-Hua; Merino, Gabriel

2018-04-16

An intriguing structural transition from the quasi-planar form of B 12 cluster upon the interaction with lithium atoms is reported. High-level computations show that the lowest energy structures of LiB 12 , Li 2 B 12 , and Li 3 B 12 have quasi-planar (C s ), tubular (D 6d ), and cage-like (C s ) geometries, respectively. The energetic cost of distorting the B 12 quasi-planar fragment is overcompensated by an enhanced electrostatic interaction between the Li cations and the tubular or cage-like B 12 fragments, which is the main reason of such drastic structural changes, resulting in the smallest tubular (Li 2 B 12 ) and cage-like (Li 3 B 12 ) boron structures reported to date. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure-Activity Relationships Predictive Models.

PubMed

Mladenović, Milan; Patsilinakos, Alexandros; Pirolli, Adele; Sabatino, Manuela; Ragno, Rino

2017-04-24

Monoamine oxidase B (MAO B) catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. Consequently, the enzyme's malfunction can induce oxidative damage to mitochondrial DNA and mediates development of Parkinson's disease. Thus, MAO B emerges as a promising target for developing pharmaceuticals potentially useful to treat this vicious neurodegenerative condition. Aiming to contribute to the development of drugs with the reversible mechanism of MAO B inhibition only, herein, an extended in silico-in vitro procedure for the selection of novel MAO B inhibitors is demonstrated, including the following: (1) definition of optimized and validated structure-based three-dimensional (3-D) quantitative structure-activity relationships (QSAR) models derived from available cocrystallized inhibitor-MAO B complexes; (2) elaboration of SAR features for either irreversible or reversible MAO B inhibitors to characterize and improve coumarin-based inhibitor activity (Protein Data Bank ID: 2V61 ) as the most potent reversible lead compound; (3) definition of structure-based (SB) and ligand-based (LB) alignment rule assessments by which virtually any untested potential MAO B inhibitor might be evaluated; (4) predictive ability validation of the best 3-D QSAR model through SB/LB modeling of four coumarin-based external test sets (267 compounds); (5) design and SB/LB alignment of novel coumarin-based scaffolds experimentally validated through synthesis and biological evaluation in vitro. Due to the wide range of molecular diversity within the 3-D QSAR training set and derived features, the selected N probe-derived 3-D QSAR model proves to be a valuable tool for virtual screening (VS) of novel MAO B inhibitors and a platform for design, synthesis and evaluation of novel active structures. Accordingly, six highly active and selective MAO B inhibitors (picomolar to low nanomolar range of activity) were disclosed as a result of rational SB/LB 3D QSAR design; therefore, D123 (IC 50 = 0.83 nM, K i = 0.25 nM) and D124 (IC 50 = 0.97 nM, K i = 0.29 nM) are potential lead candidates as anti-Parkinson's drugs.

D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions

NASA Astrophysics Data System (ADS)

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A.; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2016-09-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

D3R Grand Challenge 2015: Evaluation of Protein-Ligand Pose and Affinity Predictions

PubMed Central

Gathiaka, Symon; Liu, Shuai; Chiu, Michael; Yang, Huanwang; Stuckey, Jeanne A; Kang, You Na; Delproposto, Jim; Kubish, Ginger; Dunbar, James B.; Carlson, Heather A.; Burley, Stephen K.; Walters, W. Patrick; Amaro, Rommie E.; Feher, Victoria A.; Gilson, Michael K.

2017-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (i) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (ii) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor. PMID:27696240

Structure-based prediction of subtype selectivity of histamine H3 receptor selective antagonists in clinical trials.

PubMed

Kim, Soo-Kyung; Fristrup, Peter; Abrol, Ravinder; Goddard, William A

2011-12-27

Histamine receptors (HRs) are excellent drug targets for the treatment of diseases, such as schizophrenia, psychosis, depression, migraine, allergies, asthma, ulcers, and hypertension. Among them, the human H(3) histamine receptor (hH(3)HR) antagonists have been proposed for specific therapeutic applications, including treatment of Alzheimer's disease, attention deficit hyperactivity disorder (ADHD), epilepsy, and obesity. However, many of these drug candidates cause undesired side effects through the cross-reactivity with other histamine receptor subtypes. In order to develop improved selectivity and activity for such treatments, it would be useful to have the three-dimensional structures for all four HRs. We report here the predicted structures of four HR subtypes (H(1), H(2), H(3), and H(4)) using the GEnSeMBLE (GPCR ensemble of structures in membrane bilayer environment) Monte Carlo protocol, sampling ∼35 million combinations of helix packings to predict the 10 most stable packings for each of the four subtypes. Then we used these 10 best protein structures with the DarwinDock Monte Carlo protocol to sample ∼50 000 × 10(20) poses to predict the optimum ligand-protein structures for various agonists and antagonists. We find that E206(5.46) contributes most in binding H(3) selective agonists (5, 6, 7) in agreement with experimental mutation studies. We also find that conserved E5.46/S5.43 in both of hH(3)HR and hH(4)HR are involved in H(3)/ H(4) subtype selectivity. In addition, we find that M378(6.55) in hH(3)HR provides additional hydrophobic interactions different from hH(4)HR (the corresponding amino acid of T323(6.55) in hH(4)HR) to provide additional subtype bias. From these studies, we developed a pharmacophore model based on our predictions for known hH(3)HR selective antagonists in clinical study [ABT-239 1, GSK-189,254 2, PF-3654746 3, and BF2.649 (tiprolisant) 4] that suggests critical selectivity directing elements are: the basic proton interacting with D114(3.32), the spacer, the aromatic ring substituted with the hydrophilic or lipophilic groups interacting with lipophilic pockets in transmembranes (TMs) 3-5-6 and the aliphatic ring located in TMs 2-3-7. These 3D structures for all four HRs should help guide the rational design of novel drugs for the subtype selective antagonists and agonists with reduced side effects.

Seismic-geodynamic constraints on three-dimensional structure, vertical flow, and heat transfer in the mantle

USGS Publications Warehouse

Forte, A.M.; Woodward, R.L.

1997-01-01

Joint inversions of seismic and geodynamic data are carried out in which we simultaneously constrain global-scale seismic heterogeneity in the mantle as well as the amplitude of vertical mantle flow across the 670 km seismic discontinuity. These inversions reveal the existence of a family of three-dimensional (3-D) mantle models that satisfy the data while at the same time yielding predictions of layered mantle flow. The new 3-D mantle models we obtain demonstrate that the buoyancy forces due to the undulations of the 670 km phase-change boundary strongly inhibit the vertical flow between the upper and lower mantle. The strong stabilizing effect of the 670 km topography also has an important impact on the predicted dynamic topography of the Earth's solid surface and on the surface gravity anomalies. The new 3-D models that predict strongly or partially layered mantle flow provide essentially identical fits to the global seismic data as previous models that have, until now, predicted only whole-mantle flow. The convective vertical transport of heat across the mantle predicted on the basis of the new 3-D models shows that the heat flow is a minimum at 1000 km depth. This suggests the presence at this depth of a globally defined horizon across which the pattern of lateral heterogeneity changes rapidly. Copyright 1997 by the American Geophysical Union.

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles

PubMed Central

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe

2016-01-01

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297

ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

PubMed

Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

2016-06-20

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

Synthesis, biological evaluation, and 3D QSAR study of 2-methyl-4-oxo-3-oxetanylcarbamic acid esters as N-acylethanolamine acid amidase (NAAA) inhibitors.

PubMed

Ponzano, Stefano; Berteotti, Anna; Petracca, Rita; Vitale, Romina; Mengatto, Luisa; Bandiera, Tiziano; Cavalli, Andrea; Piomelli, Daniele; Bertozzi, Fabio; Bottegoni, Giovanni

2014-12-11

N-(2-Oxo-3-oxetanyl)carbamic acid esters have recently been reported to be noncompetitive inhibitors of the N-acylethanolamine acid amidase (NAAA) potentially useful for the treatment of pain and inflammation. In the present study, we further explored the structure-activity relationships of the carbamic acid ester side chain of 2-methyl-4-oxo-3-oxetanylcarbamic acid ester derivatives. Additional favorable features in the design of potent NAAA inhibitors have been found together with the identification of a single digit nanomolar inhibitor. In addition, we devised a 3D QSAR using the atomic property field method. The model turned out to be able to account for the structural variability and was prospectively validated by designing, synthesizing, and testing novel inhibitors. The fairly good agreement between predictions and experimental potency values points to this 3D QSAR model as the first example of quantitative structure-activity relationships in the field of NAAA inhibitors.

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

PubMed Central

Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

2013-01-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

iDBPs: a web server for the identification of DNA binding proteins.

PubMed

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-03-01

The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. http://idbps.tau.ac.il/

Comparison of FDNS liquid rocket engine plume computations with SPF/2

NASA Technical Reports Server (NTRS)

Kumar, G. N.; Griffith, D. O., II; Warsi, S. A.; Seaford, C. M.

1993-01-01

Prediction of a plume's shape and structure is essential to the evaluation of base region environments. The JANNAF standard plume flowfield analysis code SPF/2 predicts plumes well, but cannot analyze base regions. Full Navier-Stokes CFD codes can calculate both zones; however, before they can be used, they must be validated. The CFD code FDNS3D (Finite Difference Navier-Stokes Solver) was used to analyze the single plume of a Space Transportation Main Engine (STME) and comparisons were made with SPF/2 computations. Both frozen and finite rate chemistry models were employed as well as two turbulence models in SPF/2. The results indicate that FDNS3D plume computations agree well with SPF/2 predictions for liquid rocket engine plumes.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

Protein docking prediction using predicted protein-protein interface.

PubMed

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

PubMed

Núñez-Vivanco, Gabriel; Valdés-Jiménez, Alejandro; Besoaín, Felipe; Reyes-Parada, Miguel

2016-01-01

Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins. Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Measurements of d 2 n and A 1 n : Probing the neutron spin structure

DOE PAGES

Flay, D.; Posik, M.; Parno, D. S.; ...

2016-09-06

We report on the results of the E06-014 experiment performed at Jefferson Lab in Hall A, where a precision measurement of the twist-3 matrix elementmore » $$d_2$$ of the neutron ($$d_{2}^{n}$$) was conducted. This quantity represents the average color Lorentz force a struck quark experiences in a deep inelastic electron scattering event off a neutron due to its interaction with the hadronizing remnants. This color force was determined from a linear combination of the third moments of the spin structure functions $$g_1$$ and $$g_2$$ on $$^{3}$$He after nuclear corrections had been applied to these moments. The kinematics included two average $$Q^{2}$$ bins of $3.2$ GeV$$^{2}$$ and $4.3$ GeV$$^{2}$$, and Bjorken-$x$ $$0.25 \\leq x \\leq 0.90$$ covering the DIS and resonance regions. We found $$d_2^n$$ to be small and negative for $ = 3.2$ GeV$$^{2}$$, and smaller for $ = 4.3$ GeV$$^{2}$$, consistent with a lattice QCD calculation. The twist-4 matrix element $$f_{2}^{n}$$ was extracted by combining our $$d_{2}^{n}$$ with the world data on $$\\Gamma_{1}^{n} = \\int_{0}^{1} g_{1}^{n} dx$$. We found $$f_{2}^{n}$$ to be roughly an order of magnitude larger than $$d_{2}^{n}$$. Utilizing the extracted $$d_{2}^{n}$$ and $$f_{2}^{n}$$ data, we separated the color force into its electric and magnetic components, $$F_{E}^{y,n}$$ and $$F_{B}^{y,n}$$, and found them to be equal and opposite in magnitude, in agreement with instanton model predictions but not with those from QCD sum rules. Additionally, we have extracted the neutron virtual photon-nucleon asymmetry $$A_{1}^{n}$$, the structure function ratio $$g_{1}^{n}/F_{1}^{n}$$, and the quark ratios $$(\\Delta u + \\Delta \\bar{u})/(u + \\bar{u})$$ and $$(\\Delta d + \\Delta \\bar{d})/(d + \\bar{d})$$. Lastly, these results were found to be consistent with DIS world data and with the prediction of the constituent quark model but at odds with those of perturbative QCD at large $x$.« less

A Template-Based Protein Structure Reconstruction Method Using Deep Autoencoder Learning.

PubMed

Li, Haiou; Lyu, Qiang; Cheng, Jianlin

2016-12-01

Protein structure prediction is an important problem in computational biology, and is widely applied to various biomedical problems such as protein function study, protein design, and drug design. In this work, we developed a novel deep learning approach based on a deeply stacked denoising autoencoder for protein structure reconstruction. We applied our approach to a template-based protein structure prediction using only the 3D structural coordinates of homologous template proteins as input. The templates were identified for a target protein by a PSI-BLAST search. 3DRobot (a program that automatically generates diverse and well-packed protein structure decoys) was used to generate initial decoy models for the target from the templates. A stacked denoising autoencoder was trained on the decoys to obtain a deep learning model for the target protein. The trained deep model was then used to reconstruct the final structural model for the target sequence. With target proteins that have highly similar template proteins as benchmarks, the GDT-TS score of the predicted structures is greater than 0.7, suggesting that the deep autoencoder is a promising method for protein structure reconstruction.

Magnetic and electronic properties of La3 MO7 and possible polaron formation in hole-doped La3 MO7 (M  =  Ru and Os)

NASA Astrophysics Data System (ADS)

Gao, Bin; Weng, Yakui; Zhang, Jun-Jie; Zhang, Huimin; Zhang, Yang; Dong, Shuai

2017-03-01

Oxides with 4d/5d transition metal ions are physically interesting for their particular crystalline structures as well as the spin-orbit coupled electronic structures. Recent experiments revealed a series of 4d/5d transition metal oxides R 3 MO7 (R: rare earth; M: 4d/5d transition metal) with unique quasi-one-dimensional M chains. Here first-principles calculations have been performed to study the electronic structures of La3OsO7 and La3RuO7. Our study confirm both of them to be Mott insulating antiferromagnets with identical magnetic order. The reduced magnetic moments, which are much smaller than the expected value for ideal high-spin state (3 t 2g orbitals occupied), are attributed to the strong p  -  d hybridization with oxygen ions, instead of the spin-orbit coupling. The Ca-doping to La3OsO7 and La3RuO7 can not only modulate the nominal carrier density but also affect the orbital order as well as the local distortions. The Coulombic attraction and particular orbital order would prefer to form polarons, which might explain the puzzling insulating behavior of doped 5d transition metal oxides. In addition, our calculations predict that the Ca-doping can trigger ferromagnetism in La3RuO7 but not in La3OsO7.

Study on the activity of non-purine xanthine oxidase inhibitor by 3D-QSAR modeling and molecular docking

NASA Astrophysics Data System (ADS)

Li, Peizhen; Tian, Yueli; Zhai, Honglin; Deng, Fangfang; Xie, Meihong; Zhang, Xiaoyun

2013-11-01

Non-purine derivatives have been shown to be promising novel drug candidates as xanthine oxidase inhibitors. Based on three-dimensional quantitative structure-activity relationship (3D-QSAR) methods including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), two 3D-QSAR models for a series of non-purine xanthine oxidase (XO) inhibitors were established, and their reliability was supported by statistical parameters. Combined 3D-QSAR modeling and the results of molecular docking between non-purine xanthine oxidase inhibitors and XO, the main factors that influenced activity of inhibitors were investigated, and the obtained results could explain known experimental facts. Furthermore, several new potential inhibitors with higher activity predicted were designed, which based on our analyses, and were supported by the simulation of molecular docking. This study provided some useful information for the development of non-purine xanthine oxidase inhibitors with novel structures.

Exploration of enzyme-ligand interactions in CYP2D6 & 3A4 homology models and crystal structures using a novel computational approach.

PubMed

Kjellander, Britta; Masimirembwa, Collen M; Zamora, Ismael

2007-01-01

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s. This was made on a selection of 14 compounds in the data set. The prediction rates for MetaSite were 79-100% except for the CYP3A4 homology model, which picked the correct site in half of the cases. Despite differences in orientation of some important amino acids in the active sites, the MetaSite-predicted sites were the same for the different structures, with the exception of the CYP3A4 homology model. Further exploration of interactions with ligands was done by docking substrates/inhibitors in the different structures with the docking program GLUE. To address the challenge in interpreting patterns of enzyme-ligand interactions for the large number of different docking poses, a new computational tool to handle the results from the dockings was developed, in which the output highlights the relative importance of amino acids in CYP450-substrate/inhibitor interactions. The method is based on calculations of the interaction energies for each pose with the surrounding amino acids. For the CYP3A4 structures, this method was compared with consensus principal component analysis (CPCA), a commonly used method for structural comparison to evaluate the usefulness of the new method. The results from the two methods were comparable with each other, and the highlighted amino acids resemble those that were identified to have a different orientation in the compared structures. The new method has clear advantages over CPCA in that it is far simpler to interpret and there is no need for protein alignment. The methodology enables structural comparison but also gives insights on important amino acid substrate/inhibitor interactions and can therefore be very useful when suggesting modifications of new chemical entities to improve their metabolic profiles.

Frequency domain and full waveform time domain inversion of ground based magnetometer, electrometer and incoherent scattering radar arrays to image strongly heterogenous 3-D Earth structure, ionospheric structure, and to predict the intensity of GICs in the power grid

NASA Astrophysics Data System (ADS)

Schultz, A.; Imamura, N.; Bonner, L. R., IV; Cosgrove, R. B.

2016-12-01

Ground-based magnetometer and electrometer arrays provide the means to probe the structure of the Earth's interior, the interactions of space weather with the ionosphere, and to anticipate the intensity of geomagnetically induced currents (GICs) in power grids. We present a local-to-continental scale view of a heterogeneous 3-D crust and mantle as determined from magnetotelluric (MT) observations across arrays of ground-based electric and magnetic field sensors. MT impedance tensors describe the relationship between electric and magnetic fields at a given site, thus implicitly they contain all known information on the 3-D electrical resistivity structure beneath and surrounding that site. By using multivariate transfer functions to project real-time magnetic observatory network data to areas surrounding electric power grids, and by projecting those magnetic fields through MT impedance tensors, the projected magnetic field can be transformed into predictions of electric fields along the path of the transmission lines, an essential element of predicting the intensity of GICs in the grid. Finally, we explore GICs, i.e. Earth-ionosphere coupling directly in the time-domain. We consider the fully coupled EM system, where we allow for a non-stationary ionospheric source field of arbitrary complexity above a 3-D Earth. We solve the simultaneous inverse problem for 3-D Earth conductivity and source field structure directly in the time domain. In the present work, we apply this method to magnetotelluric data obtained from a synchronously operating array of 25 MT stations that collected continuous MT waveform data in the interior of Alaska during the autumn and winter of 2015 under the footprint of the Poker Flat (Alaska) Incoherent Scattering Radar (PFISR). PFISR data yield functionals of the ionospheric electric field and ionospheric conductivity that constrain the MT source field. We show that in this region conventional robust MT processing methods struggle to produce reliable MT response functions at periods much greater than about 2,000 s, a consequence, we believe, of the complexity of the ionospheric source fields in this high latitude setting. This provides impetus for direct waveform inversion methods that dispense with typical parametric assumptions made about the MT source fields.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

Delta: a new web-based 3D genome visualization and analysis platform.

PubMed

Tang, Bixia; Li, Feifei; Li, Jing; Zhao, Wenming; Zhang, Zhihua

2018-04-15

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Delta features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs. Finally, by visually comparing the 3D model of the β-globin gene locus and its annotation, we speculated a plausible transitory interaction pattern in the locus. Experimental evidence was found to support this speculation by literature survey. This served as an example of intuitive hypothesis testing with the help of Delta. Delta is freely accessible from http://delta.big.ac.cn, and the source code is available at https://github.com/zhangzhwlab/delta. zhangzhihua@big.ac.cn. Supplementary data are available at Bioinformatics online.

3D toroidal physics: testing the boundaries of symmetry breaking

NASA Astrophysics Data System (ADS)

Spong, Don

2014-10-01

Toroidal symmetry is an important concept for plasma confinement; it allows the existence of nested flux surface MHD equilibria and conserved invariants for particle motion. However, perfect symmetry is unachievable in realistic toroidal plasma devices. For example, tokamaks have toroidal ripple due to discrete field coils, optimized stellarators do not achieve exact quasi-symmetry, the plasma itself continually seeks lower energy states through helical 3D deformations, and reactors will likely have non-uniform distributions of ferritic steel near the plasma. Also, some level of designed-in 3D magnetic field structure is now anticipated for most concepts in order to lead to a stable, steady-state fusion reactor. Such planned 3D field structures can take many forms, ranging from tokamaks with weak 3D ELM-suppression fields to stellarators with more dominant 3D field structures. There is considerable interest in the development of unified physics models for the full range of 3D effects. Ultimately, the questions of how much symmetry breaking can be tolerated and how to optimize its design must be addressed for all fusion concepts. Fortunately, significant progress is underway in theory, computation and plasma diagnostics on many issues such as magnetic surface quality, plasma screening vs. amplification of 3D perturbations, 3D transport, influence on edge pedestal structures, MHD stability effects, modification of fast ion-driven instabilities, prediction of energetic particle heat loads on plasma-facing materials, effects of 3D fields on turbulence, and magnetic coil design. A closely coupled program of simulation, experimental validation, and design optimization is required to determine what forms and amplitudes of 3D shaping and symmetry breaking will be compatible with future fusion reactors. The development of models to address 3D physics and progress in these areas will be described. This work is supported both by the US Department of Energy under Contract DE-AC05-00OR22725 with UT-Battelle, LLC and under the US DOE SciDAC GSEP Center.

3D reconstruction modeling of bulk heterojunction organic photovoltaic cells: Effect of the complexity of the boundary on the morphology

NASA Astrophysics Data System (ADS)

Kim, Sung-Jin; Jeong, Daun; Kim, SeongMin; Choi, Yeong Suk; Ihn, Soo-Ghang; Yun, Sungyoung; Lim, Younhee; Lee, Eunha; Park, Gyeong-Su

2016-02-01

Although the morphology of the active layer in bulk heterojunction organic photovoltaic (BHJ-OPV) cells is critical for determining the quantum efficiency (QE), predicting the real QE for a 3-dimensional (3D) morphology has long been difficult because structural information on the composition complexity of donor (D): acceptor (A) blends with small domain size is limited to 2D observations via various image-processing techniques. To overcome this, we reconstruct the 3D morphology by using an isotropic statistical approach based on 2D energy-filtered transmission electron microscopy (EF-TEM) images. This new reconstruction method is validated to obtain the internal QE by using a dynamic Monte Carlo simulation in the BHJ-OPV system with different additives such as 4 vol% 1-chloronaphthalene (CN) and 4 vol% 1,8-diiodooctane (DIO) (compared to the case of no additive); the resulting trend is compared with the experimental QE. Therefore, our developed method can be used to predict the real charge transport performance in the OPV system accurately.

Intramolecular BSSE and dispersion affect the structure of a dipeptide conformer

NASA Astrophysics Data System (ADS)

Hameed, Rabia; Khan, Afsar; van Mourik, Tanja

2018-05-01

B3LYP and MP2 calculations with the commonly-used 6-31+G(d) basis set predict qualitatively different structures for the Tyr-Gly conformer book1, which is the most stable conformer identified in a previous study. The structures differ mainly in the ψtyr Ramachandran angle (138° in the B3LYP structure and 120° in the MP2 structure). The causes for the discrepant structures are attributed to missing dispersion in the B3LYP calculations and large intramolecular BSSE in the MP2 calculations. The correct ψtyr value is estimated to be 130°. The MP2/6-31+G(d) profile identified an additional conformer, not present on the B3LYP surface, with a ψtyr value of 96° and a more folded structure. This minimum is, however, likely an artefact of large intramolecular BSSE values. We recommend the use of basis sets of at least quadruple-zeta quality in density functional theory (DFT), DFTaugmented with an empirical dispersion term (DFT-D) and second-order Møller-Plesset perturbation theory (MP2 ) calculations in cases where intramolecular BSSE is expected to be large.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

DockBench as docking selector tool: the lesson learned from D3R Grand Challenge 2015.

PubMed

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2016-09-01

Structure-based drug design (SBDD) has matured within the last two decades as a valuable tool for the optimization of low molecular weight lead compounds to highly potent drugs. The key step in SBDD requires knowledge of the three-dimensional structure of the target-ligand complex, which is usually determined by X-ray crystallography. In the absence of structural information for the complex, SBDD relies on the generation of plausible molecular docking models. However, molecular docking protocols suffer from inaccuracies in the description of the interaction energies between the ligand and the target molecule, and often fail in the prediction of the correct binding mode. In this context, the appropriate selection of the most accurate docking protocol is absolutely relevant for the final molecular docking result, even if addressing this point is absolutely not a trivial task. D3R Grand Challenge 2015 has represented a precious opportunity to test the performance of DockBench, an integrate informatics platform to automatically compare RMDS-based molecular docking performances of different docking/scoring methods. The overall performance resulted in the blind prediction are encouraging in particular for the pose prediction task, in which several complex were predicted with a sufficient accuracy for medicinal chemistry purposes.

Molecular Dynamic Simulation and Inhibitor Prediction of Cysteine Synthase Structured Model as a Potential Drug Target for Trichomoniasis

PubMed Central

Singh, Satendra; Singh, Atul Kumar; Gautam, Budhayash

2013-01-01

In our presented research, we made an attempt to predict the 3D model for cysteine synthase (A2GMG5_TRIVA) using homology-modeling approaches. To investigate deeper into the predicted structure, we further performed a molecular dynamics simulation for 10 ns and calculated several supporting analysis for structural properties such as RMSF, radius of gyration, and the total energy calculation to support the predicted structured model of cysteine synthase. The present findings led us to conclude that the proposed model is stereochemically stable. The overall PROCHECK G factor for the homology-modeled structure was −0.04. On the basis of the virtual screening for cysteine synthase against the NCI subset II molecule, we present the molecule 1-N, 4-N-bis [3-(1H-benzimidazol-2-yl) phenyl] benzene-1,4-dicarboxamide (ZINC01690699) having the minimum energy score (−13.0 Kcal/Mol) and a log P value of 6 as a potential inhibitory molecule used to inhibit the growth of T. vaginalis infection. PMID:24073401

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

PubMed

Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna

2014-12-01

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Combining theoretical and experimental data to decipher CFTR 3D structures and functions.

PubMed

Hoffmann, Brice; Elbahnsi, Ahmad; Lehn, Pierre; Décout, Jean-Luc; Pietrucci, Fabio; Mornon, Jean-Paul; Callebaut, Isabelle

2018-05-19

Cryo-electron microscopy (cryo-EM) has recently provided invaluable experimental data about the full-length cystic fibrosis transmembrane conductance regulator (CFTR) 3D structure. However, this experimental information deals with inactive states of the channel, either in an apo, quiescent conformation, in which nucleotide-binding domains (NBDs) are widely separated or in an ATP-bound, yet closed conformation. Here, we show that 3D structure models of the open and closed forms of the channel, now further supported by metadynamics simulations and by comparison with the cryo-EM data, could be used to gain some insights into critical features of the conformational transition toward active CFTR forms. These critical elements lie within membrane-spanning domains but also within NBD1 and the N-terminal extension, in which conformational plasticity is predicted to occur to help the interaction with filamin, one of the CFTR cellular partners.

Large scale CIV3 calculations of fine-structure energy levels, oscillator strengths, and lifetimes in Fe XIV and Ni XVI

NASA Astrophysics Data System (ADS)

Gupta, G. P.; Msezane, A. Z.

2005-01-01

We have performed large scale CIV3 calculations of excitation energies from ground states for 109 fine-structure levels as well as of oscillator strengths and radiative decay rates for all electric-dipole-allowed and intercombination transitions among the (1s 22s 22p 6)3s 23p( 2P 0), 3s3p 2( 2S, 2P, 2D, 4P), 3s 23d( 2D), 3p 3( 4S 0, 2P 0, 2D 0), 3s3p( 3P 0)3d( 2P 0, 2D 0, 2F 0, 4P 0, 4D 0, 4F 0), 3s3p( 1P 0)3d( 2P 0, 2D 0, 2F 0), 3p 2( 1S)3d( 2D), 3p 2( 1D)3d( 2S, 2P, 2D), 3p 2( 3P)3d( 2P, 2D, 4P), 3s3d 2( 2S, 2P, 2D, 4P), 3p3d 2( 1S)( 2P 0), 3p3d 2( 1D)( 2P 0, 2D 0, 2F 0), 3p3d 2( 1G)( 2F 0), 3p3d 2( 3P)( 2P 0, 2D 0, 4S 0, 4P 0, 4D 0), 3p3d 2( 3F)( 2D 0, 2F 0, 4D 0, 4F 0), 3s 24s( 2S), 3s 24p( 2P 0), 3s 24d( 2D), 3s 24f( 2F 0), 3s3p( 3P 0)4s( 2P 0, 4P 0), and 3s3p( 1P 0)4s( 2P 0) states of Fe XIV and Ni XVI. These states are represented by very extensive configuration-interaction (CI) wavefunctions obtained using the CIV3 computer code of Hibbert. The relativistic effects in intermediate coupling are incorporated by means of the Breit-Pauli Hamiltonian which consists of the nonrelativistic term plus the one-body mass correction, Darwin term, and spin-orbit, spin-other-orbit, and spin-spin operators. The errors which often occur with sophisticated ab initio atomic structure calculations are reduced. Our calculated excitation energies, including their ordering, are in excellent agreement with the available experimental results for both of the ions studied. From our transition probabilities, we have also calculated radiative lifetimes of the lowest 37 fine-structure levels in Fe XIV and Ni XVI and compared them with available theoretical and experimental results. The mixing among several fine-structure levels is found to be so strong that the correct identification of these levels becomes very difficult. We predict new data for several levels where no other theoretical and/or experimental results are available. We hope that our extensive calculations will be useful to experimentalists in identifying the fine-structure levels in their future work.

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

PubMed

Bhagavat, Raghu; Sankar, Santhosh; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2018-03-06

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Investigation of advancing front method for generating unstructured grid

NASA Technical Reports Server (NTRS)

Thomas, A. M.; Tiwari, S. N.

1992-01-01

The advancing front technique is used to generate an unstructured grid about simple aerodynamic geometries. Unstructured grids are generated using VGRID2D and VGRID3D software. Specific problems considered are a NACA 0012 airfoil, a bi-plane consisting of two NACA 0012 airfoil, a four element airfoil in its landing configuration, and an ONERA M6 wing. Inviscid time dependent solutions are computed on these geometries using USM3D and the results are compared with standard test results obtained by other investigators. A grid convergence study is conducted for the NACA 0012 airfoil and compared with a structured grid. A structured grid is generated using GRIDGEN software and inviscid solutions computed using CFL3D flow solver. The results obtained by unstructured grid for NACA 0012 airfoil showed an asymmetric distribution of flow quantities, and a fine distribution of grid was required to remove this asymmetry. On the other hand, the structured grid predicted a very symmetric distribution, but when the total number of points were compared to obtain the same results it was seen that structured grid required more grid points.

Low-cost structured-light based 3D capture system design

NASA Astrophysics Data System (ADS)

Dong, Jing; Bengtson, Kurt R.; Robinson, Barrett F.; Allebach, Jan P.

2014-03-01

Most of the 3D capture products currently in the market are high-end and pricey. They are not targeted for consumers, but rather for research, medical, or industrial usage. Very few aim to provide a solution for home and small business applications. Our goal is to fill in this gap by only using low-cost components to build a 3D capture system that can satisfy the needs of this market segment. In this paper, we present a low-cost 3D capture system based on the structured-light method. The system is built around the HP TopShot LaserJet Pro M275. For our capture device, we use the 8.0 Mpixel camera that is part of the M275. We augment this hardware with two 3M MPro 150 VGA (640 × 480) pocket projectors. We also describe an analytical approach to predicting the achievable resolution of the reconstructed 3D object based on differentials and small signal theory, and an experimental procedure for validating that the system under test meets the specifications for reconstructed object resolution that are predicted by our analytical model. By comparing our experimental measurements from the camera-projector system with the simulation results based on the model for this system, we conclude that our prototype system has been correctly configured and calibrated. We also conclude that with the analytical models, we have an effective means for specifying system parameters to achieve a given target resolution for the reconstructed object.

Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5.

PubMed

Vijaya Prabhu, Sitrarasu; Singh, Sanjeev Kumar

2018-05-28

Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R 2  = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q 2  = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).

Cutting Materials in Half: A Graph Theory Approach for Generating Crystal Surfaces and Its Prediction of 2D Zeolites

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

Witman, Matthew; Ling, Sanliang; Boyd, Peter

Scientific interest in two-dimensional (2D) materials, ranging from graphene and other single layer materials to atomically thin crystals, is quickly increasing for a large variety of technological applications. While in silico design approaches have made a large impact in the study of 3D crystals, algorithms designed to discover atomically thin 2D materials from their parent 3D materials are by comparison more sparse. Here, we hypothesize that determining how to cut a 3D material in half (i.e., which Miller surface is formed) by severing a minimal number of bonds or a minimal amount of total bond energy per unit area canmore » yield insight into preferred crystal faces. We answer this question by implementing a graph theory technique to mathematically formalize the enumeration of minimum cut surfaces of crystals. While the algorithm is generally applicable to different classes of materials, we focus on zeolitic materials due to their diverse structural topology and because 2D zeolites have promising catalytic and separation performance compared to their 3D counterparts. We report here a simple descriptor based only on structural information that predicts whether a zeolite is likely to be synthesizable in the 2D form and correctly identifies the expressed surface in known layered 2D zeolites. The discovery of this descriptor allows us to highlight other zeolites that may also be synthesized in the 2D form that have not been experimentally realized yet. Finally, our method is general since the mathematical formalism can be applied to find the minimum cut surfaces of other crystallographic materials such as metal-organic frameworks, covalent-organic frameworks, zeolitic-imidazolate frameworks, metal oxides, etc.« less

Cutting Materials in Half: A Graph Theory Approach for Generating Crystal Surfaces and Its Prediction of 2D Zeolites.

PubMed

Witman, Matthew; Ling, Sanliang; Boyd, Peter; Barthel, Senja; Haranczyk, Maciej; Slater, Ben; Smit, Berend

2018-02-28

Scientific interest in two-dimensional (2D) materials, ranging from graphene and other single layer materials to atomically thin crystals, is quickly increasing for a large variety of technological applications. While in silico design approaches have made a large impact in the study of 3D crystals, algorithms designed to discover atomically thin 2D materials from their parent 3D materials are by comparison more sparse. We hypothesize that determining how to cut a 3D material in half (i.e., which Miller surface is formed) by severing a minimal number of bonds or a minimal amount of total bond energy per unit area can yield insight into preferred crystal faces. We answer this question by implementing a graph theory technique to mathematically formalize the enumeration of minimum cut surfaces of crystals. While the algorithm is generally applicable to different classes of materials, we focus on zeolitic materials due to their diverse structural topology and because 2D zeolites have promising catalytic and separation performance compared to their 3D counterparts. We report here a simple descriptor based only on structural information that predicts whether a zeolite is likely to be synthesizable in the 2D form and correctly identifies the expressed surface in known layered 2D zeolites. The discovery of this descriptor allows us to highlight other zeolites that may also be synthesized in the 2D form that have not been experimentally realized yet. Finally, our method is general since the mathematical formalism can be applied to find the minimum cut surfaces of other crystallographic materials such as metal-organic frameworks, covalent-organic frameworks, zeolitic-imidazolate frameworks, metal oxides, etc.

Cutting Materials in Half: A Graph Theory Approach for Generating Crystal Surfaces and Its Prediction of 2D Zeolites

PubMed Central

2018-01-01

Scientific interest in two-dimensional (2D) materials, ranging from graphene and other single layer materials to atomically thin crystals, is quickly increasing for a large variety of technological applications. While in silico design approaches have made a large impact in the study of 3D crystals, algorithms designed to discover atomically thin 2D materials from their parent 3D materials are by comparison more sparse. We hypothesize that determining how to cut a 3D material in half (i.e., which Miller surface is formed) by severing a minimal number of bonds or a minimal amount of total bond energy per unit area can yield insight into preferred crystal faces. We answer this question by implementing a graph theory technique to mathematically formalize the enumeration of minimum cut surfaces of crystals. While the algorithm is generally applicable to different classes of materials, we focus on zeolitic materials due to their diverse structural topology and because 2D zeolites have promising catalytic and separation performance compared to their 3D counterparts. We report here a simple descriptor based only on structural information that predicts whether a zeolite is likely to be synthesizable in the 2D form and correctly identifies the expressed surface in known layered 2D zeolites. The discovery of this descriptor allows us to highlight other zeolites that may also be synthesized in the 2D form that have not been experimentally realized yet. Finally, our method is general since the mathematical formalism can be applied to find the minimum cut surfaces of other crystallographic materials such as metal–organic frameworks, covalent-organic frameworks, zeolitic-imidazolate frameworks, metal oxides, etc. PMID:29532024

Cutting Materials in Half: A Graph Theory Approach for Generating Crystal Surfaces and Its Prediction of 2D Zeolites

DOE PAGES

Witman, Matthew; Ling, Sanliang; Boyd, Peter; ...

2018-02-06

Scientific interest in two-dimensional (2D) materials, ranging from graphene and other single layer materials to atomically thin crystals, is quickly increasing for a large variety of technological applications. While in silico design approaches have made a large impact in the study of 3D crystals, algorithms designed to discover atomically thin 2D materials from their parent 3D materials are by comparison more sparse. Here, we hypothesize that determining how to cut a 3D material in half (i.e., which Miller surface is formed) by severing a minimal number of bonds or a minimal amount of total bond energy per unit area canmore » yield insight into preferred crystal faces. We answer this question by implementing a graph theory technique to mathematically formalize the enumeration of minimum cut surfaces of crystals. While the algorithm is generally applicable to different classes of materials, we focus on zeolitic materials due to their diverse structural topology and because 2D zeolites have promising catalytic and separation performance compared to their 3D counterparts. We report here a simple descriptor based only on structural information that predicts whether a zeolite is likely to be synthesizable in the 2D form and correctly identifies the expressed surface in known layered 2D zeolites. The discovery of this descriptor allows us to highlight other zeolites that may also be synthesized in the 2D form that have not been experimentally realized yet. Finally, our method is general since the mathematical formalism can be applied to find the minimum cut surfaces of other crystallographic materials such as metal-organic frameworks, covalent-organic frameworks, zeolitic-imidazolate frameworks, metal oxides, etc.« less

Stiffness analysis of glued connection of the timber-concrete structure

NASA Astrophysics Data System (ADS)

Daňková, Jana; Mec, Pavel; Majstríková, Tereza

2016-01-01

This paper presents results of experimental and mathematical analysis of stiffness characteristics of a composite timber-concrete structure. The composite timberconcrete structure presented herein is non-typical compared to similar types of building structures. The interaction between the timber and concrete part of the composite cross-section is not based on metal connecting elements, but it is ensured by a glued-in perforated mesh made of plywood. The paper presents results of experimental and mathematical analysis for material alternatives of the solution of the glued joint. The slip modulus values were determined experimentally. Data obtained from the experiment evaluated by means of regression analysis. Test results were also used as input data for the compilation of a 3D model of a composite structure by means of the 3D finite element model. On the basis of result evaluation, it can be stated that the stress-deformation behaviour at shear loading of this specific timber-concrete composite structure can be affected by the type of glue used. Parameters of the 3D model of both alternative of the structure represent well the behaviour of the composite structure and the model can be used for predicting design parameters of a building structure.

On the Use of 3dB Qualification Margin for Structural Parts on Expendable Launch Vehicles

NASA Technical Reports Server (NTRS)

Yunis, Isam

2007-01-01

The standard random vibration qualification test used for Expendable Launch Vehicle components is Maximum Predicted Environment (MPE) + 6dB for a duration of 4 times the service life of the part. This can be a severe qualification test for these fatigue-sensitive structures. This paper uses flight data from several launch vehicles to establish that reducing the qualification approach to MPE+3dB for the duration of the peak environment (1x life) is valid for fatigue-sensitive structural components. Items that can be classified as fatigue-sensitive are probes, ducts, tubing, bellows, hoses, and any non-functional structure. Non-functional structure may be flight critical or carry fluid, but it cannot include any moving parts or electronics. This reduced qualification approach does not include primary or secondary structure which would be exclusively designed by peak loads, either transient or quasi-static, that are so large and of so few cycles as to make fatigue a moot point.

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

PubMed Central

Zhou, Nannan; Xu, Yuan; Liu, Xian; Wang, Yulan; Peng, Jianlong; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2015-01-01

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. PMID:26110383

Exploration of tetrahedral structures in silicate cathodes using a motif-network scheme

DOE PAGES

Zhao, Xin; Wu, Shunqing; Lv, Xiaobao; ...

2015-10-26

Using a motif-network search scheme, we studied the tetrahedral structures of the dilithium/disodium transition metal orthosilicates A 2MSiO 4 with A = Li or Na and M = Mn, Fe or Co. In addition to finding all previously reported structures, we discovered many other different tetrahedral-network-based crystal structures which are highly degenerate in energy. In addition, these structures can be classified into structures with 1D, 2D and 3D M-Si-O frameworks. A clear trend of the structural preference in different systems was revealed and possible indicators that affect the structure stabilities were introduced. For the case of Na systems which havemore » been much less investigated in the literature relative to the Li systems, we predicted their ground state structures and found evidence for the existence of new structural motifs.« less

Spectroscopic and DFT studies of bis-3-hydroxypyridinium and bis-3-hydroxymethylpyridinium dibromides with tetramethylene linker

NASA Astrophysics Data System (ADS)

Komasa, Anna

2018-01-01

Experimental and theoretical IR, Raman, UV-Vis, 1H and 13C NMR spectra of 1,4-di(3-hydroxypyridinium)butane dibromide and 1,4-di(3-hydroxymethylpyridinium)butane dibromide were obtained and analyzed. Optimized geometrical structures of the studied compounds were calculated by B3LYP method using 6-311++G(d,p) basis set and employed to determine the theoretical wavenumbers and intensities of IR and Raman spectra. The frequency assignments were supported by the potential energy distribution (PED) analysis. The significant role of the intermolecular interactions and the hydrogen bond was revealed on the basis of IR spectra. The calculated GIAO/B3LYP/6-311++G(d,p) isotropic magnetic shielding constants were used to predict the 1H and 13C chemical shifts for the optimized structures. Accuracy of the prediction of 1H and 13C chemical shifts was significantly improved by a simulation of the solvent in calculations. On the basis of UV-Vis spectra the acid-base equilibrium in the water solution of 1,4-di(3-hydroxypyridinium)butane dibromide was found.

Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations

NASA Technical Reports Server (NTRS)

Wang, Li; Diskin, Boris; Biedron, Robert T.; Nielsen, Eric J.; Bauchau, Olivier A.

2017-01-01

A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.

MINEMOTION3D: A new set of Programs for Predicting Ground Motion From Explosions in Complex 3D Media

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Bonner, J. L.; Orrey, J. L.; Yang, X.

2004-12-01

Predicting ground motion from complicated mining explosions is important for mines developing new blasting programs in regions where vibrations must be kept below certain levels. Additionally, predicting ground motion from mining explosions in complex 3D media is important for moment estimation for nuclear test treaty monitoring. Both problems have been addressed under the development of a new series of numerical prediction programs called MINEMOTION3D including 1) Generalized Fourier Methods to generate Green's functions in 3D media for a moment tensor source implementation and 2) MineSeis3D, a program that simulates seismograms for delay-fired mining explosions with a linear relationship between signals from small size individual shots. To test the programs, local recordings (5 - 23 km) of three production shots at a mine in northern Minnesota were compared to synthetic waveforms in 3D media. A non-zero value of the moment tensor component M12 was considered, to introduce a horizontal spall component into the waveform synthesis when the Green's functions were generated for each model. Methods using seismic noise crosscorrelation for improved inter-element subsurface structure estimation were also evaluated. Comparison of the observed and synthetic waveforms shows promising results. The shape and arrival times of the normalized synthetic and observed waveforms are similar for most of the stations. The synthetic and observed waveform amplitude fit is best for the vertical components in the mean 3D model and worst for the transversal components. The observed effect of spall on the waveform spectra was weak in the case of fragmentation delay fired commercial explosions. Commercial applications of the code could provide data needed for designing explosions which do not exceed ground vibration requirements posed by the U.S. Department of the Interior, Office of Surface Mining.

Commercial turbofan engine exhaust nozzle flow analyses using PAB3D

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Uenishi, K.; Carlson, John R.; Keith, B. D.

1992-01-01

Recent developments of a three-dimensional (PAB3D) code have paved the way for a computational investigation of complex aircraft aerodynamic components. The PAB3D code was developed for solving the simplified Reynolds Averaged Navier-Stokes equations in a three-dimensional multiblock/multizone structured mesh domain. The present analysis was applied to commercial turbofan exhaust flow systems. Solution sensitivity to grid density is presented. Laminar flow solutions were developed for all grids and two-equation k-epsilon solutions were developed for selected grids. Static pressure distributions, mass flow and thrust quantities were calculated for on-design engine operating conditions. Good agreement between predicted surface static pressures and experimental data was observed at different locations. Mass flow was predicted within 0.2 percent of experimental data. Thrust forces were typically within 0.4 percent of experimental data.

Compression of stereoscopic video using MPEG-2

NASA Astrophysics Data System (ADS)

Puri, A.; Kollarits, Richard V.; Haskell, Barry G.

1995-10-01

Many current as well as emerging applications in areas of entertainment, remote operations, manufacturing industry and medicine can benefit from the depth perception offered by stereoscopic video systems which employ two views of a scene imaged under the constraints imposed by human visual system. Among the many challenges to be overcome for practical realization and widespread use of 3D/stereoscopic systems are good 3D displays and efficient techniques for digital compression of enormous amounts of data while maintaining compatibility with normal video decoding and display systems. After a brief introduction to the basics of 3D/stereo including issues of depth perception, stereoscopic 3D displays and terminology in stereoscopic imaging and display, we present an overview of tools in the MPEG-2 video standard that are relevant to our discussion on compression of stereoscopic video, which is the main topic of this paper. Next, we outilne the various approaches for compression of stereoscopic video and then focus on compatible stereoscopic video coding using MPEG-2 Temporal scalability concepts. Compatible coding employing two different types of prediction structures become potentially possible, disparity compensated prediction and combined disparity and motion compensated predictions. To further improve coding performance and display quality, preprocessing for reducing mismatch between the two views forming stereoscopic video is considered. Results of simulations performed on stereoscopic video of normal TV resolution are then reported comparing the performance of two prediction structures with the simulcast solution. It is found that combined disparity and motion compensated prediction offers the best performance. Results indicate that compression of both views of stereoscopic video of normal TV resolution appears feasible in a total of 6 to 8 Mbit/s. We then discuss regarding multi-viewpoint video, a generalization of stereoscopic video. Finally, we describe ongoing efforts within MPEG-2 to define a profile for stereoscopic video coding, as well as, the promise of MPEG-4 in addressing coding of multi-viewpoint video.

Compression of stereoscopic video using MPEG-2

NASA Astrophysics Data System (ADS)

Puri, Atul; Kollarits, Richard V.; Haskell, Barry G.

1995-12-01

Many current as well as emerging applications in areas of entertainment, remote operations, manufacturing industry and medicine can benefit from the depth perception offered by stereoscopic video systems which employ two views of a scene imaged under the constraints imposed by human visual system. Among the many challenges to be overcome for practical realization and widespread use of 3D/stereoscopic systems are good 3D displays and efficient techniques for digital compression of enormous amounts of data while maintaining compatibility with normal video decoding and display systems. After a brief introduction to the basics of 3D/stereo including issues of depth perception, stereoscopic 3D displays and terminology in stereoscopic imaging and display, we present an overview of tools in the MPEG-2 video standard that are relevant to our discussion on compression of stereoscopic video, which is the main topic of this paper. Next, we outline the various approaches for compression of stereoscopic video and then focus on compatible stereoscopic video coding using MPEG-2 Temporal scalability concepts. Compatible coding employing two different types of prediction structures become potentially possible, disparity compensated prediction and combined disparity and motion compensated predictions. To further improve coding performance and display quality, preprocessing for reducing mismatch between the two views forming stereoscopic video is considered. Results of simulations performed on stereoscopic video of normal TV resolution are then reported comparing the performance of two prediction structures with the simulcast solution. It is found that combined disparity and motion compensated prediction offers the best performance. Results indicate that compression of both views of stereoscopic video of normal TV resolution appears feasible in a total of 6 to 8 Mbit/s. We then discuss regarding multi-viewpoint video, a generalization of stereoscopic video. Finally, we describe ongoing efforts within MPEG-2 to define a profile for stereoscopic video coding, as well as, the promise of MPEG-4 in addressing coding of multi-viewpoint video.

Electro-mechanical Properties of Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Anantram, M. P.; Yang, Liu; Han, Jie; Liu, J. P.; Saubum Subhash (Technical Monitor)

1998-01-01

We present a simple picture to understand the bandgap variation of carbon nanotubes with small tensile and torsional strains, independent of chirality. Using this picture, we are able to predict a simple dependence of d(Bandoap)$/$d(strain) on the value of $(N_x-N_y)*mod 3$, for semiconducting tubes. We also predict a novel change in sign of d(Bandgap)$/$d(strain) as a function of tensile strain arising from a change in the value of $q$ corresponding to the minimum bandgap. These calculations are complemented by calculations of the change in bandgap using energy minimized structures, and some important differences are discussed. The calculations are based on the $i$ electron approximation.

Multiple Exciton Generation in Semiconductor Nanostructures: DFT-based Computation

NASA Astrophysics Data System (ADS)

Mihaylov, Deyan; Kryjevski, Andrei; Kilin, Dmitri; Kilina, Svetlana; Vogel, Dayton

Multiple exciton generation (MEG) in nm-sized H-passivated Si nanowires (NWs), and quasi 2D nanofilms depends strongly on the degree of the core structural disorder as shown by the perturbation theory calculations based on the DFT simulations. In perturbation theory, we work to the 2nd order in the electron-photon coupling and in the (approximate) RPA-screened Coulomb interaction. We also include the effect of excitons for which we solve Bethe-Salpeter Equation. To describe MEG we calculate exciton-to-biexciton as well as biexciton-to-exciton rates and quantum efficiency (QE). We consider 3D arrays of Si29H36 quantum dots, NWs, and quasi 2D silicon nanofilms, all with both crystalline and amorphous core structures. Efficient MEG with QE of 1.3 up to 1.8 at the photon energy of about 3Egap is predicted in these nanoparticles except for the crystalline NW and film where QE ~=1. MEG in the amorphous nanoparticles is enhanced by the electron localization due to structural disorder. The exciton effects significantly red-shift QE vs. photon energy curves. Nm-sized a-Si NWs and films are predicted to have effective MEG within the solar spectrum range. Also, we find efficient MEG in the chiral single-wall Carbon nanotubes and in a perovskite nanostructure.

Synthesis of crystalline and amorphous, particle-agglomerated 3-D nanostructures of Al and Si oxides by femtosecond laser and the prediction of these particle sizes

NASA Astrophysics Data System (ADS)

Sivayoganathan, Mugunthan; Tan, Bo; Venkatakrishnan, Krishnan

2012-11-01

We report a single step technique of synthesizing particle-agglomerated, amorphous 3-D nanostructures of Al and Si oxides on powder-fused aluminosilicate ceramic plates and a simple novel method of wafer-foil ablation to fabricate crystalline nanostructures of Al and Si oxides at ambient conditions. We also propose a particle size prediction mechanism to regulate the size of vapor-condensed agglomerated nanoparticles in these structures. Size characterization studies performed on the agglomerated nanoparticles of fabricated 3-D structures showed that the size distributions vary with the fluence-to-threshold ratio. The variation in laser parameters leads to varying plume temperature, pressure, amount of supersaturation, nucleation rate, and the growth rate of particles in the plume. The novel wafer-foil ablation technique could promote the possibilities of fabricating oxide nanostructures with varying Al/Si ratio, and the crystallinity of these structures enhances possible applications. The fabricated nanostructures of Al and Si oxides could have great potentials to be used in the fabrication of low power-consuming complementary metal-oxide-semiconductor circuits and in Mn catalysts to enhance the efficiency of oxidation on ethylbenzene to acetophenone in the super-critical carbon dioxide.

Synthesis of crystalline and amorphous, particle-agglomerated 3-D nanostructures of Al and Si oxides by femtosecond laser and the prediction of these particle sizes.

PubMed

Sivayoganathan, Mugunthan; Tan, Bo; Venkatakrishnan, Krishnan

2012-11-09

We report a single step technique of synthesizing particle-agglomerated, amorphous 3-D nanostructures of Al and Si oxides on powder-fused aluminosilicate ceramic plates and a simple novel method of wafer-foil ablation to fabricate crystalline nanostructures of Al and Si oxides at ambient conditions. We also propose a particle size prediction mechanism to regulate the size of vapor-condensed agglomerated nanoparticles in these structures. Size characterization studies performed on the agglomerated nanoparticles of fabricated 3-D structures showed that the size distributions vary with the fluence-to-threshold ratio. The variation in laser parameters leads to varying plume temperature, pressure, amount of supersaturation, nucleation rate, and the growth rate of particles in the plume. The novel wafer-foil ablation technique could promote the possibilities of fabricating oxide nanostructures with varying Al/Si ratio, and the crystallinity of these structures enhances possible applications. The fabricated nanostructures of Al and Si oxides could have great potentials to be used in the fabrication of low power-consuming complementary metal-oxide-semiconductor circuits and in Mn catalysts to enhance the efficiency of oxidation on ethylbenzene to acetophenone in the super-critical carbon dioxide.

Synthesis of crystalline and amorphous, particle-agglomerated 3-D nanostructures of Al and Si oxides by femtosecond laser and the prediction of these particle sizes

PubMed Central

2012-01-01

We report a single step technique of synthesizing particle-agglomerated, amorphous 3-D nanostructures of Al and Si oxides on powder-fused aluminosilicate ceramic plates and a simple novel method of wafer-foil ablation to fabricate crystalline nanostructures of Al and Si oxides at ambient conditions. We also propose a particle size prediction mechanism to regulate the size of vapor-condensed agglomerated nanoparticles in these structures. Size characterization studies performed on the agglomerated nanoparticles of fabricated 3-D structures showed that the size distributions vary with the fluence-to-threshold ratio. The variation in laser parameters leads to varying plume temperature, pressure, amount of supersaturation, nucleation rate, and the growth rate of particles in the plume. The novel wafer-foil ablation technique could promote the possibilities of fabricating oxide nanostructures with varying Al/Si ratio, and the crystallinity of these structures enhances possible applications. The fabricated nanostructures of Al and Si oxides could have great potentials to be used in the fabrication of low power-consuming complementary metal-oxide-semiconductor circuits and in Mn catalysts to enhance the efficiency of oxidation on ethylbenzene to acetophenone in the super-critical carbon dioxide. PMID:23140103

Molecule kernels: a descriptor- and alignment-free quantitative structure-activity relationship approach.

PubMed

Mohr, Johannes A; Jain, Brijnesh J; Obermayer, Klaus

2008-09-01

Quantitative structure activity relationship (QSAR) analysis is traditionally based on extracting a set of molecular descriptors and using them to build a predictive model. In this work, we propose a QSAR approach based directly on the similarity between the 3D structures of a set of molecules measured by a so-called molecule kernel, which is independent of the spatial prealignment of the compounds. Predictors can be build using the molecule kernel in conjunction with the potential support vector machine (P-SVM), a recently proposed machine learning method for dyadic data. The resulting models make direct use of the structural similarities between the compounds in the test set and a subset of the training set and do not require an explicit descriptor construction. We evaluated the predictive performance of the proposed method on one classification and four regression QSAR datasets and compared its results to the results reported in the literature for several state-of-the-art descriptor-based and 3D QSAR approaches. In this comparison, the proposed molecule kernel method performed better than the other QSAR methods.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

PubMed

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Two-Dimensional Stoichiometric Boron Oxides as a Versatile Platform for Electronic Structure Engineering.

PubMed

Zhang, Ruiqi; Li, Zhenyu; Yang, Jinlong

2017-09-21

Oxides of two-dimensional (2D) atomic crystals have been widely studied due to their unique properties. In most 2D oxides, oxygen acts as a functional group, which makes it difficult to control the degree of oxidation. Because borophene is an electron-deficient system, it is expected that oxygen will be intrinsically incorporated into the basal plane of borophene, forming stoichiometric 2D boron oxide (BO) structures. By using first-principles global optimization, we systematically explore structures and properties of 2D BO systems with well-defined degrees of oxidation. Stable B-O-B and OB 3 tetrahedron structure motifs are identified in these structures. Interesting properties, such as strong linear dichroism, Dirac node-line (DNL) semimetallicity, and negative differential resistance, have been predicted for these systems. Our results demonstrate that 2D BO represents a versatile platform for electronic structure engineering via tuning the stoichiometric degree of oxidation, which leads to various technological applications.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Effect of 3-D viscoelastic structure on post-seismic relaxation from the 2004 M = 9.2 Sumatra earthquake

USGS Publications Warehouse

Pollitz, F.; Banerjee, P.; Grijalva, K.; Nagarajan, B.; Burgmann, R.

2008-01-01

The 2004 M=9.2 Sumatra-Andaman earthquake profoundly altered the state of stress in a large volume surrounding the ???1400 km long rupture. Induced mantle flow fields and coupled surface deformation are sensitive to the 3-D rheology structure. To predict the post-seismic motions from this earthquake, relaxation of a 3-D spherical viscoelastic earth model is simulated using the theory of coupled normal modes. The quasi-static deformation basis set and solution on the 3-D model is constructed using: a spherically stratified viscoelastic earth model with a linear stress-strain relation; an aspherical perturbation in viscoelastic structure; a 'static'mode basis set consisting of Earth's spheroidal and toroidal free oscillations; a "viscoelastic" mode basis set; and interaction kernels that describe the coupling among viscoelastic and static modes. Application to the 2004 Sumatra-Andaman earthquake illustrates the profound modification of the post-seismic flow field at depth by a slab structure and similarly large effects on the near-field post-seismic deformation field at Earth's surface. Comparison with post-seismic GPS observations illustrates the extent to which viscoelastic relaxation contributes to the regional post-seismic deformation. ?? Journal compilation ?? 2008 RAS.

Four-Phase Dendritic Model for the Prediction of Macrosegregation, Shrinkage Cavity, and Porosity in a 55-Ton Ingot

NASA Astrophysics Data System (ADS)

Ge, Honghao; Ren, Fengli; Li, Jun; Han, Xiujun; Xia, Mingxu; Li, Jianguo

2017-03-01

A four-phase dendritic model was developed to predict the macrosegregation, shrinkage cavity, and porosity during solidification. In this four-phase dendritic model, some important factors, including dendritic structure for equiaxed crystals, melt convection, crystals sedimentation, nucleation, growth, and shrinkage of solidified phases, were taken into consideration. Furthermore, in this four-phase dendritic model, a modified shrinkage criterion was established to predict shrinkage porosity (microporosity) of a 55-ton industrial Fe-3.3 wt pct C ingot. The predicted macrosegregation pattern and shrinkage cavity shape are in a good agreement with experimental results. The shrinkage cavity has a significant effect on the formation of positive segregation in hot top region, which generally forms during the last stage of ingot casting. The dendritic equiaxed grains also play an important role on the formation of A-segregation. A three-dimensional laminar structure of A-segregation in industrial ingot was, for the first time, predicted by using a 3D case simulation.

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

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.

Three-dimensional thermal structure and seismogenesis in the Tohoku and Hokkaido subduction system

NASA Astrophysics Data System (ADS)

van Keken, P. E.; Kita, S.; Nakajima, J.; Bengtson, A. K.; Hacker, B. R.; Abers, G. A.

2010-12-01

The Northern Japan arc is characterized by fast subduction of old oceanic lithosphere. The high density instrumentation and high seismicity make this an ideal natural laboratory to study the interplay between subduction zone dynamics, dehydration, migration of fluids, and seismogenesis. In this study we use high resolution finite element models to predict the thermal structure of the subduction slab below Tohoku (Northern Honshu) and Hokkaido. These models allow us to predict the pressure, temperature and mineralogy of the subducted crust and mantle. We use these models to predict the (p,T) conditions of earthquakes that are relocated with a precision of around 1 km by double difference techniques. Below Northern Hokkaido and Tohoku we find that the earthquake activity is strong in crust and the uppermost mantle for temperatures < 450 C. Above this temperature earthquakes occur more sporadically and have significantly reduced integrated seismic moment. The strongest 3D variations in this arc occur below southern Hokkaido. This 200 km wide region is characterized by a change in trench geometry, anomalously low heatflow and an anomalous velocity structure in the mantle wedge. Tomographic imaging suggest that continental crust is subducted to significant depth, thereby insulating the subducting slab from the hot mantle wedge at least at intermediate depths. The thermal insulation is also suggested by the deepening of the earthquakes in the slab (Kita et al., EPSL, 2010). This region may be characterized by active crustal erosion which would lead to a further blanketing of the crust by a sedimentary layer. Further modifications in thermal structure are possible due to the 3D wedge flow that is generated by the along-arc variations in trench geometry. We quantitatively verify the relative importance of these processes using 2D and 3D dynamical models. Without the seismically imaged crustal structure the earthquake temperatures are significantly elevated compared to the Tohoku and (northern) Hokkaido sections. If we take the modified crustal structure into account we find a (p,T) pattern that is quite similar to that in the other sections, suggesting that the processes that lead to earthquakes in crust and uppermost mantle of the downgoing slab are similar across the northern Japan arc.

Multi-Scale Analyses of Three Dimensional Woven Composite 3D Shell With a Cut Out Circle

NASA Astrophysics Data System (ADS)

Nguyen, Duc Hai; Wang, Hu

2018-06-01

A composite material are made by combining two or more constituent materials to obtain the desired material properties of each product type. The matrix material which can be polymer and fiber is used as reinforcing material. Currently, the polymer matrix is widely used in many different fields with differently designed structures such as automotive structures and aviation, aerospace, marine, etc. because of their excellent mechanical properties; in addition, they possess the high level of hardness and durability together with a significant reduction in weight compared to traditional materials. However, during design process of structure, there will be many interruptions created for the purpose of assembling the structures together or for many other design purposes. Therefore, when this structure is subject to load-bearing, its failure occurs at these interruptions due to stress concentration. This paper proposes multi-scale modeling and optimization strategies in evaluation of the effectiveness of fiber orientation in an E-glass/Epoxy woven composite 3D shell with circular holes at the center investigated by FEA results. A multi-scale model approach was developed to predict the mechanical behavior of woven composite 3D shell with circular holes at the center with different designs of material and structural parameters. Based on the analysis result of laminae, we have found that the 3D shell with fiber direction of 450 shows the best stress and strain bearing capacity. Thus combining several layers of 450 fiber direction in a multi-layer composite 3D shell reduces the stresses concentrated on the cuts of the structures.

Kohn-Sham Band Structure Benchmark Including Spin-Orbit Coupling for 2D and 3D Solids

NASA Astrophysics Data System (ADS)

Huhn, William; Blum, Volker

2015-03-01

Accurate electronic band structures serve as a primary indicator of the suitability of a material for a given application, e.g., as electronic or catalytic materials. Computed band structures, however, are subject to a host of approximations, some of which are more obvious (e.g., the treatment of the exchange-correlation of self-energy) and others less obvious (e.g., the treatment of core, semicore, or valence electrons, handling of relativistic effects, or the accuracy of the underlying basis set used). We here provide a set of accurate Kohn-Sham band structure benchmarks, using the numeric atom-centered all-electron electronic structure code FHI-aims combined with the ``traditional'' PBE functional and the hybrid HSE functional, to calculate core, valence, and low-lying conduction bands of a set of 2D and 3D materials. Benchmarks are provided with and without effects of spin-orbit coupling, using quasi-degenerate perturbation theory to predict spin-orbit splittings. This work is funded by Fritz-Haber-Institut der Max-Planck-Gesellschaft.

Ligand-based 3D QSAR analysis of reactivation potency of mono- and bis-pyridinium aldoximes toward VX-inhibited rat acetylcholinesterase.

PubMed

Dolezal, Rafael; Korabecny, Jan; Malinak, David; Honegr, Jan; Musilek, Kamil; Kuca, Kamil

2015-03-01

To predict unknown reactivation potencies of 12 mono- and bis-pyridinium aldoximes for VX-inhibited rat acetylcholinesterase (rAChE), three-dimensional quantitative structure-activity relationship (3D QSAR) analysis has been carried out. Utilizing molecular interaction fields (MIFs) calculated by molecular mechanical (MMFF94) and quantum chemical (B3LYP/6-31G*) methods, two satisfactory ligand-based CoMFA models have been developed: 1. R(2)=0.9989, Q(LOO)(2)=0.9090, Q(LTO)(2)=0.8921, Q(LMO(20%))(2)=0.8853, R(ext)(2)=0.9259, SDEP(ext)=6.8938; 2. R(2)=0.9962, Q(LOO)(2)=0.9368, Q(LTO)(2)=0.9298, Q(LMO(20%))(2)=0.9248, R(ext)(2)=0.8905, SDEP(ext)=6.6756. High statistical significance of the 3D QSAR models has been achieved through the application of several data noise reduction techniques (i.e. smart region definition SRD, fractional factor design FFD, uninformative/iterative variable elimination UVE/IVE) on the original MIFs. Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied. The contour maps as well as the predicted reactivation potencies resulting from 3D QSAR analyses help better understand which structural features are associated with increased reactivation potency of studied compounds. Copyright © 2014 Elsevier Inc. All rights reserved.

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Hochhalter, Jacob D.; Newman, John A.; Leser, William P.; Warner, James E.; Wawrzynek, Paul A.; Yuan, Fuh-Gwo

2015-01-01

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

A general structure-property relationship to predict the enthalpy of vaporisation at ambient temperatures.

PubMed

Oberg, T

2007-01-01

The vapour pressure is the most important property of an anthropogenic organic compound in determining its partitioning between the atmosphere and the other environmental media. The enthalpy of vaporisation quantifies the temperature dependence of the vapour pressure and its value around 298 K is needed for environmental modelling. The enthalpy of vaporisation can be determined by different experimental methods, but estimation methods are needed to extend the current database and several approaches are available from the literature. However, these methods have limitations, such as a need for other experimental results as input data, a limited applicability domain, a lack of domain definition, and a lack of predictive validation. Here we have attempted to develop a quantitative structure-property relationship (QSPR) that has general applicability and is thoroughly validated. Enthalpies of vaporisation at 298 K were collected from the literature for 1835 pure compounds. The three-dimensional (3D) structures were optimised and each compound was described by a set of computationally derived descriptors. The compounds were randomly assigned into a calibration set and a prediction set. Partial least squares regression (PLSR) was used to estimate a low-dimensional QSPR model with 12 latent variables. The predictive performance of this model, within the domain of application, was estimated at n=560, q2Ext=0.968 and s=0.028 (log transformed values). The QSPR model was subsequently applied to a database of 100,000+ structures, after a similar 3D optimisation and descriptor generation. Reliable predictions can be reported for compounds within the previously defined applicability domain.

CDOCKER and lambda λ -dynamics for prospective prediction in D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Ding, Xinqiang; Hayes, Ryan L.; Vilseck, Jonah Z.; Charles, Murchtricia K.; Brooks, Charles L.

2018-01-01

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and λ-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 Å. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 Å for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For λ-dynamics techniques, including multisite λ-dynamics (MSλD), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

Investigating the Energetic Ordering of Stable and Metastable TiO 2 Polymorphs Using DFT+ U and Hybrid Functionals

DOE PAGES

Curnan, Matthew T.; Kitchin, John R.

2015-08-12

Prediction of transition metal oxide BO 2 (B = Ti, V, etc.) polymorph energetic properties is critical to tunable material design and identifying thermodynamically accessible structures. Determining procedures capable of synthesizing particular polymorphs minimally requires prior knowledge of their relative energetic favorability. Information concerning TiO 2 polymorph relative energetic favorability has been ascertained from experimental research. In this study, the consistency of first-principles predictions and experimental results involving the relative energetic ordering of stable (rutile), metastable (anatase and brookite), and unstable (columbite) TiO 2 polymorphs is assessed via density functional theory (DFT). Considering the issues involving electron–electron interaction and chargemore » delocalization in TiO 2 calculations, relative energetic ordering predictions are evaluated over trends varying Ti Hubbard U 3d or exact exchange fraction parameter values. Energetic trends formed from varying U 3d predict experimentally consistent energetic ordering over U 3d intervals when using GGA-based functionals, regardless of pseudopotential selection. Given pertinent linear response calculated Hubbard U values, these results enable TiO 2 polymorph energetic ordering prediction. Here, the hybrid functional calculations involving rutile–anatase relative energetics, though demonstrating experimentally consistent energetic ordering over exact exchange fraction ranges, are not accompanied by predicted fractions, for a first-principles methodology capable of calculating exact exchange fractions precisely predicting TiO 2 polymorph energetic ordering is not available.« less

Comparative analysis of CDPK family in maize, Arabidopsis, rice and sorghum revealed potential targets for drought tolerance improvement

NASA Astrophysics Data System (ADS)

Mittal, Shikha; Mallikarjuna, Mallana Gowdra; Rao, Atmakuri R.; Jain, Prashant A.; Dash, Prasanta K.; Thirunavukkarasu, Nepolean

2017-12-01

Calcium dependent protein kinases (CDPKs) play major role in regulation of plant growth and development in response to various stresses including drought. A set of 32 CDPK genes identified in maize were further used for searching of orthologs in the model plant Arabidopsis (72) and major food crops such as rice (78) and sorghum (91). We comprehensively investigated the phylogenetic relationship, annotations, gene duplications, gene structure, divergence time, 3-D protein structures and tissue-specific drought induced expression of CDPK genes in all four species. Variation in intron frequency among these species likely contributed to the functional diversity of CDPK genes to various stress responses. Protein kinase and protein kinase C phosphorylation site domains were the most conserved motifs identified in all species. Four groups were identified from the sequence-based phylogenetic analysis, in which maize CDPKs were clustered in group III. The time of divergence (Ka/Ks) analysis revealed that the CDPKs were evolved through stabilizing selection. Expression data showed that the CDPK genes were highly expressed in leaf of maize, rice, and sorghum whereas in Arabidopsis the maximum expression was observed in root. 3-D protein structure were predicted for the nine genes (Arabidopsis: 2, maize: 2, rice: 3 and sorghum: 2) showing differential expression in at least three species. The predicted 3-D structures were further evaluated and validated by Ramachandran plot, ANOLEA, ProSA and Verify-3D. The superimposed 3-D structure of drought-related orthologous proteins retained similar folding pattern owing to their conserved nature. Functional annotation revealed the involvement of CDPK genes in various pathways such as osmotic homeostasis, cell protection and root growth. The interactions of CDPK genes in various pathways play crucial role in imparting drought tolerance through different ABA and MAPK signalling cascades. Our studies suggest that these selected candidate genes could be targeted in development of drought tolerant cultivars in maize, rice and sorghum through appropriate breeding approaches. Our comparative experiments of CDPK genes could also be extended in the drought stress breeding programmes of the related species.

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking.

PubMed

Chen, H F; Dong, X C; Zen, B S; Gao, K; Yuan, S G; Panaye, A; Doucet, J P; Fan, B T

2003-08-01

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework.

PubMed

Glusman, Gustavo; Rose, Peter W; Prlić, Andreas; Dougherty, Jennifer; Duarte, José M; Hoffman, Andrew S; Barton, Geoffrey J; Bendixen, Emøke; Bergquist, Timothy; Bock, Christian; Brunk, Elizabeth; Buljan, Marija; Burley, Stephen K; Cai, Binghuang; Carter, Hannah; Gao, JianJiong; Godzik, Adam; Heuer, Michael; Hicks, Michael; Hrabe, Thomas; Karchin, Rachel; Leman, Julia Koehler; Lane, Lydie; Masica, David L; Mooney, Sean D; Moult, John; Omenn, Gilbert S; Pearl, Frances; Pejaver, Vikas; Reynolds, Sheila M; Rokem, Ariel; Schwede, Torsten; Song, Sicheng; Tilgner, Hagen; Valasatava, Yana; Zhang, Yang; Deutsch, Eric W

2017-12-18

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

PubMed Central

Myint, Kyaw Z.; Xie, Xiang-Qun

2015-01-01

This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

Directing Matter: Toward Atomic-Scale 3D Nanofabrication.

PubMed

Jesse, Stephen; Borisevich, Albina Y; Fowlkes, Jason D; Lupini, Andrew R; Rack, Philip D; Unocic, Raymond R; Sumpter, Bobby G; Kalinin, Sergei V; Belianinov, Alex; Ovchinnikova, Olga S

2016-06-28

Enabling memristive, neuromorphic, and quantum-based computing as well as efficient mainstream energy storage and conversion technologies requires the next generation of materials customized at the atomic scale. This requires full control of atomic arrangement and bonding in three dimensions. The last two decades witnessed substantial industrial, academic, and government research efforts directed toward this goal through various lithographies and scanning-probe-based methods. These technologies emphasize 2D surface structures, with some limited 3D capability. Recently, a range of focused electron- and ion-based methods have demonstrated compelling alternative pathways to achieving atomically precise manufacturing of 3D structures in solids, liquids, and at interfaces. Electron and ion microscopies offer a platform that can simultaneously observe dynamic and static structures at the nano- and atomic scales and also induce structural rearrangements and chemical transformation. The addition of predictive modeling or rapid image analytics and feedback enables guiding these in a controlled manner. Here, we review the recent results that used focused electron and ion beams to create free-standing nanoscale 3D structures, radiolysis, and the fabrication potential with liquid precursors, epitaxial crystallization of amorphous oxides with atomic layer precision, as well as visualization and control of individual dopant motion within a 3D crystal lattice. These works lay the foundation for approaches to directing nanoscale level architectures and offer a potential roadmap to full 3D atomic control in materials. In this paper, we lay out the gaps that currently constrain the processing range of these platforms, reflect on indirect requirements, such as the integration of large-scale data analysis with theory, and discuss future prospects of these technologies.

Multi-scale modeling of tsunami flows and tsunami-induced forces

NASA Astrophysics Data System (ADS)

Qin, X.; Motley, M. R.; LeVeque, R. J.; Gonzalez, F. I.

2016-12-01

The modeling of tsunami flows and tsunami-induced forces in coastal communities with the incorporation of the constructed environment is challenging for many numerical modelers because of the scale and complexity of the physical problem. A two-dimensional (2D) depth-averaged model can be efficient for modeling of waves offshore but may not be accurate enough to predict the complex flow with transient variance in vertical direction around constructed environments on land. On the other hand, using a more complex three-dimensional model is much more computational expensive and can become impractical due to the size of the problem and the meshing requirements near the built environment. In this study, a 2D depth-integrated model and a 3D Reynolds Averaged Navier-Stokes (RANS) model are built to model a 1:50 model-scale, idealized community, representative of Seaside, OR, USA, for which existing experimental data is available for comparison. Numerical results from the two numerical models are compared with each other as well as experimental measurement. Both models predict the flow parameters (water level, velocity, and momentum flux in the vicinity of the buildings) accurately, in general, except for time period near the initial impact, where the depth-averaged models can fail to capture the complexities in the flow. Forces predicted using direct integration of predicted pressure on structural surfaces from the 3D model and using momentum flux from the 2D model with constructed environment are compared, which indicates that force prediction from the 2D model is not always reliable in such a complicated case. Force predictions from integration of the pressure are also compared with forces predicted from bare earth momentum flux calculations to reveal the importance of incorporating the constructed environment in force prediction models.

Bioreactor-engineered cancer tissue-like structures mimic phenotypes, gene expression profiles and drug resistance patterns observed "in vivo".

PubMed

Hirt, Christian; Papadimitropoulos, Adam; Muraro, Manuele G; Mele, Valentina; Panopoulos, Evangelos; Cremonesi, Eleonora; Ivanek, Robert; Schultz-Thater, Elke; Droeser, Raoul A; Mengus, Chantal; Heberer, Michael; Oertli, Daniel; Iezzi, Giandomenica; Zajac, Paul; Eppenberger-Castori, Serenella; Tornillo, Luigi; Terracciano, Luigi; Martin, Ivan; Spagnoli, Giulio C

2015-09-01

Anticancer compound screening on 2D cell cultures poorly predicts "in vivo" performance, while conventional 3D culture systems are usually characterized by limited cell proliferation, failing to produce tissue-like-structures (TLS) suitable for drug testing. We addressed engineering of TLS by culturing cancer cells in porous scaffolds under perfusion flow. Colorectal cancer (CRC) HT-29 cells were cultured in 2D, on collagen sponges in static conditions or in perfused bioreactors, or injected subcutaneously in immunodeficient mice. Perfused 3D (p3D) cultures resulted in significantly higher (p < 0.0001) cell proliferation than static 3D (s3D) cultures and yielded more homogeneous TLS, with morphology and phenotypes similar to xenografts. Transcriptome analysis revealed a high correlation between xenografts and p3D cultures, particularly for gene clusters regulating apoptotic processes and response to hypoxia. Treatment with 5-Fluorouracil (5-FU), a frequently used but often clinically ineffective chemotherapy drug, induced apoptosis, down-regulation of anti-apoptotic genes (BCL-2, TRAF1, and c-FLIP) and decreased cell numbers in 2D, but only "nucleolar stress" in p3D and xenografts. Conversely, BCL-2 inhibitor ABT-199 induced cytotoxic effects in p3D but not in 2D cultures. Our findings advocate the importance of perfusion flow in 3D cultures of tumor cells to efficiently mimic functional features observed "in vivo" and to test anticancer compounds. Copyright © 2015 Elsevier Ltd. All rights reserved.

5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

NASA Astrophysics Data System (ADS)

Doulamis, A.; Doulamis, N.; Ioannidis, C.; Chrysouli, C.; Grammalidis, N.; Dimitropoulos, K.; Potsiou, C.; Stathopoulou, E.-K.; Ioannides, M.

2015-08-01

Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics.

On the vibrational spectra and structural parameters of methyl, silyl, and germyl azide from theoretical predictions and experimental data.

PubMed

Durig, Douglas T; Durig, M S; Durig, James R

2005-05-01

The infrared and Raman spectra of methyl, silyl, and germyl azide (XN3 where X=CH3, SiH3 and GeH3) have been predicted from ab initio calculations with full electron correlation by second order perturbation theory (MP2) and hybrid density function theory (DFT) by the B3LYP method with a variety of basis sets. These predicted data are compared to previously reported experimental data and complete vibrational assignments are provided for all three molecules. It is shown that several of the assignments recently proposed [J. Mol. Struct. (Theochem.) 434 (1998) 1] for methyl azide are not correct. Structural parameters for CH3N3 and GeH3N3 have been obtained by combining the previously reported microwave rotational constants with the ab initio MP2/6-311+G(d,p) predicted values. These "adjusted r0" parameters have very small uncertainties of +/-0.003 A for the XH distances and a maximum of +/-0.005 A for the heavy atom distances and +/-0.5 degrees for the angles. The predicted distance for the terminal NN bond which is nearly a triple bond is much better predicted by the B3LYP calculations, whereas the fundamental frequencies are better predicted by the scaled ab initio calculations. The results are discussed and compared to those obtained for some similar molecules.

SU-E-T-424: Feasibility of 3D Printed Radiological Equivalent Customizable Tissue Like Materials

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

Johnson, D; Ferreira, C; Ahmad, S

Purpose: To investigate the feasibility of 3D printing CT# specific radiological equivalent tissue like materials. Methods: A desktop 3D printer was utilized to create a series of 3 cm x 3 cm x 2 cm PLA plastic blocks of varying fill densities. The fill pattern was selected to be hexagonal (Figure 1). A series of blocks was filled with paraffin and compared to a series filled with air. The blocks were evaluated with a “GE Lightspeed” 16 slice CT scanner and average CT# of the centers of the materials was determined. The attenuation properties of the subsequent blocks were alsomore » evaluated through their isocentric irradiation via “TrueBeam” accelerator under six beam energies. Blocks were placed upon plastic-water slabs of 4 cm in thickness assuring electronic equilibrium and data was collected via Sun Nuclear “Edge” diode detector. Relative changes in dose were compared with those predicted by Varian “Eclipse” TPS. Results: The CT# of 3D printed blocks was found to be a controllable variable. The fill material was able to narrow the range of variability in each sample. The attenuation of the block tracked with the density of the total fill structure. Assigned CT values in the TPS were seen to fall within an expected range predicted by the CT scans of the 3D printed blocks. Conclusion: We have demonstrated that it is possible to 3D print materials of varying tissue equivalencies, and that these materials have radiological properties that are customizable and predictable.« less

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

An improved stochastic fractal search algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Sun, Chuan; Wang, Bin; Wang, Xiaojun

2018-05-03

Protein structure prediction (PSP) is a significant area for biological information research, disease treatment, and drug development and so on. In this paper, three-dimensional structures of proteins are predicted based on the known amino acid sequences, and the structure prediction problem is transformed into a typical NP problem by an AB off-lattice model. This work applies a novel improved Stochastic Fractal Search algorithm (ISFS) to solve the problem. The Stochastic Fractal Search algorithm (SFS) is an effective evolutionary algorithm that performs well in exploring the search space but falls into local minimums sometimes. In order to avoid the weakness, Lvy flight and internal feedback information are introduced in ISFS. In the experimental process, simulations are conducted by ISFS algorithm on Fibonacci sequences and real peptide sequences. Experimental results prove that the ISFS performs more efficiently and robust in terms of finding the global minimum and avoiding getting stuck in local minimums.

Improved hybrid optimization algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

2014-07-01

A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

Protein structure prediction with local adjust tabu search algorithm

PubMed Central

2014-01-01

Background Protein folding structure prediction is one of the most challenging problems in the bioinformatics domain. Because of the complexity of the realistic protein structure, the simplified structure model and the computational method should be adopted in the research. The AB off-lattice model is one of the simplification models, which only considers two classes of amino acids, hydrophobic (A) residues and hydrophilic (B) residues. Results The main work of this paper is to discuss how to optimize the lowest energy configurations in 2D off-lattice model and 3D off-lattice model by using Fibonacci sequences and real protein sequences. In order to avoid falling into local minimum and faster convergence to the global minimum, we introduce a novel method (SATS) to the protein structure problem, which combines simulated annealing algorithm and tabu search algorithm. Various strategies, such as the new encoding strategy, the adaptive neighborhood generation strategy and the local adjustment strategy, are adopted successfully for high-speed searching the optimal conformation corresponds to the lowest energy of the protein sequences. Experimental results show that some of the results obtained by the improved SATS are better than those reported in previous literatures, and we can sure that the lowest energy folding state for short Fibonacci sequences have been found. Conclusions Although the off-lattice models is not very realistic, they can reflect some important characteristics of the realistic protein. It can be found that 3D off-lattice model is more like native folding structure of the realistic protein than 2D off-lattice model. In addition, compared with some previous researches, the proposed hybrid algorithm can more effectively and more quickly search the spatial folding structure of a protein chain. PMID:25474708

Predicting activation energy of thermolysis of polynitro arenes through molecular structure.

PubMed

Keshavarz, Mohammad Hossein; Pouretedal, Hamid Reza; Shokrolahi, Arash; Zali, Abbas; Semnani, Abolfazl

2008-12-15

The paper presents a new method for activation energy or the Arrhenius parameter E(a) of the thermolysis in the condensed state for different polynitro arenes as an important class of energetic molecules. The methodology assumes that E(a) of a polynitro arene with general formula C(a)H(b)N(c)O(d) can be expressed as a function of optimized elemental composition as well as the contribution of specific molecular structural parameters. The new method can predict E(a) of the thermolysis under conditions of Soviet Manometric Method (SMM), which can be related to the other convenient methods. The new correlation has the root mean square (rms) and the average deviations of 13.79 and 11.94kJ/mol, respectively, for 20 polynitro arenes with different molecular structures. The proposed new method can also be used to predict E(a) of three polynitro arenes, i.e. 2,2',2'',4,4',4'',6,6',6''-nonanitro-1,1':3',1''-terphenyl (NONA), 3,3'-diamino-2,2',4,4',6,6'-hexanitro-1,1'-biphenyl-3,3'-diamine (DIPAM) and N,N-bis(2,4-dinitrophenyl)-2,4,6-trinitroaniline (NTFA), which have complex molecular structures.

A quantum chemical calculation of the potential energy surface in the formation of HOSO 2 from OH + SO 2

NASA Astrophysics Data System (ADS)

Sitha, Sanyasi; Jewell, Linda L.; Piketh, Stuart J.; Fourie, Gerhard

2011-01-01

The formation of HOSO 2 from OH and SO 2 has been thoroughly investigated using several different methods (MP2=Full, MP2=FC, B3LYP, HF and composite G∗ methods) and basis sets (6-31G(d,p), 6-31++G(d,p), 6-31++G(2d,2p), 6-31++G(2df,2p) and aug-cc-pVnZ). We have found two different possible transition state structures, one of which is a true transition state since it has a higher energy than the reactants and products (MP2=Full, MP2=FC and HF), while the other is not a true transition state since it has an energy which lies between that of the reactants and products (B3LYP and B3LYP based methods). The transition state structure (from MP2) has a twist angle of the OH fragment relative to the SO bond of the SO 2 fragment of -50.0°, whereas this angle is 26.7° in the product molecule. Examination of the displacement vectors confirms that this is a true transition state structure. The MP2=Full method with a larger basis set (MP2=Full/6-31++G(2df,2p)) predicts the enthalpy of reaction to be -112.8 kJ mol -1 which is close to the experimental value of -113.3 ± 6 kJ mol -1, and predicts a rather high barrier of 20.0 kJ mol -1. When the TS structure obtained by the MP2 method is used as the input for calculating the energetics using the QCISD/6-31++G(2df,2p) method, a barrier of 4.1 kJ mol -1 is obtained (ZPE corrected). The rate constant calculated from this barrier is 1.3 × 10 -13 cm 3 molecule -1 s -1. We conclude that while the MP2 methods correctly predict the TS from a structural point of view, higher level energy corrections are needed for estimation of exact barrier height.

Research Update: Electrical monitoring of cysts using organic electrochemical transistors a

NASA Astrophysics Data System (ADS)

Huerta, M.; Rivnay, J.; Ramuz, M.; Hama, A.; Owens, R. M.

2015-03-01

Organotypic three-dimensional (3D) cell culture models have the potential to act as surrogate tissues in vitro, both for basic research and for drug discovery/toxicology. 3D cultures maintain not only 3D architecture but also cell-cell and cell extracellular matrix interactions, particularly when grown in cysts or spheroids. Characterization of cell cultures grown in 3D formats, however, provides a significant challenge for cell biologists due to the incompatibility of these structures with commonly found optical or electronic monitoring systems. Electronic impedance spectroscopy is a cell culture monitoring technique with great potential; however, it has not been possible to integrate 3D cultures with commercially available systems to date. Cyst-like 3D cultures are particularly challenging due to their small size and difficulty in manipulation. Herein, we demonstrate isolation of cyst-like 3D cultures by capillarity and subsequent integration with the organic electrochemical transistor for monitoring the integrity of these structures. We show not only that this versatile device can be adapted to the cyst format for measuring resistance and, therefore, the quality of the cysts, but also can be used for quantitative monitoring of the effect of toxic compounds on cells in a 3D format. The ability to quantitatively predict effects of drugs on 3D cultures in vitro has large future potential for the fields of drug discovery and toxicology.

Research Update: Electrical monitoring of cysts using organic electrochemical transistors

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

Huerta, M.; Rivnay, J.; Ramuz, M.

2015-03-01

Organotypic three-dimensional (3D) cell culture models have the potential to act as surrogate tissues in vitro, both for basic research and for drug discovery/toxicology. 3D cultures maintain not only 3D architecture but also cell-cell and cell extracellular matrix interactions, particularly when grown in cysts or spheroids. Characterization of cell cultures grown in 3D formats, however, provides a significant challenge for cell biologists due to the incompatibility of these structures with commonly found optical or electronic monitoring systems. Electronic impedance spectroscopy is a cell culture monitoring technique with great potential; however, it has not been possible to integrate 3D cultures withmore » commercially available systems to date. Cyst-like 3D cultures are particularly challenging due to their small size and difficulty in manipulation. Herein, we demonstrate isolation of cyst-like 3D cultures by capillarity and subsequent integration with the organic electrochemical transistor for monitoring the integrity of these structures. We show not only that this versatile device can be adapted to the cyst format for measuring resistance and, therefore, the quality of the cysts, but also can be used for quantitative monitoring of the effect of toxic compounds on cells in a 3D format. The ability to quantitatively predict effects of drugs on 3D cultures in vitro has large future potential for the fields of drug discovery and toxicology.« less

NMR, FT-IR, Raman and UV-Vis spectroscopic investigation and DFT study of 6-Bromo-3-Pyridinyl Boronic Acid

NASA Astrophysics Data System (ADS)

Dikmen, Gökhan; Alver, Özgür

2015-11-01

Possible stable conformers and geometrical molecular structures of 6-Bromo-3-Pyridinyl Boronic acid (6B3PBA; C5H5BBrNO2) were studied experimentally and theoretically using FT-IR and Raman spectroscopic methods. FT-IR and Raman spectra were recorded in the region of 4000-400 cm-1 and 3700-400 cm-1, respectively. The structural properties were investigated further, using 1H, 13C, 1H coupled 13C, HETCOR, COSY and APT NMR techniques. The optimized geometric structures were searched by Becke-3-Lee-Yang-Parr (B3LYP) hybrid density functional theory method with 6-311++G(d, p) basis set. Vibrational wavenumbers of 6B3PBA were calculated whereby B3LYP density functional methods including 6-311++G(d, p), 6-311G(d, p), 6-311G(d), 6-31G(d, p) and 6-31G(d) basis sets. The comparison of the experimentally and theoretically obtained results using mean absolute error and experimental versus calculated correlation coefficients for the vibrational wavenumbers indicates that B3LYP method with 6-311++G(d, p) gives more satisfactory results for predicting vibrational wavenumbers when compared to the 6-311G(d, p), 6-311G(d), 6-31G(d, p) and 6-31G(d) basis sets. However, this method and none of the mentioned methods here seem suitable for the calculations of OH stretching modes, most likely because increasing unharmonicity in the high wave number region and possible intra and inter molecular interactions at OH edges lead some deviations between experimental and theoretical results. Moreover, reliable vibrational assignments were made on the basis of total energy distribution (TED) calculated using scaled quantum mechanical (SQM) method.

Surface 3D Micro Free Forms: Multifunctional Microstructured Mesoporous α-Alumina by in Situ Slip Casting Using Excimer Laser Ablated Polycarbonate Molds.

PubMed

Rowthu, Sriharitha; Böhlen, Karl; Bowen, Paul; Hoffmann, Patrik

2015-11-11

Ceramic surface microstructuring is a rapidly growing field with a variety of applications in tribology, wetting, biology, and so on. However, there are limitations to large-area microstructuring and fabrication of three-dimensional (3D) micro free forms. Here, we present a route to obtain intricate surface structures through in situ slip casting using polydimethylsiloxane (PDMS) negative molds which are replicated from excimer laser ablated polycarbonate (PC) master molds. PC sheets are ablated with a nanosecond KrF (λ = 248 nm) excimer laser mask projection system to obtain micron-scale 3D surface features over a large area of up to 3 m(2). Complex surface structures that include 3D free forms such as 3D topography of Switzerland, shallow structures such as diffractive optical elements (60 nm step) and conical micropillars have been obtained. The samples are defect-free produced with thicknesses of up to 10 mm and 120 mm diameter. The drying process of the slip cast alumina slurry takes place as a one-dimensional process, through surface evaporation and water permeation through the PDMS membrane. This allows homogeneous one-dimensional shrinkage during the drying process, independent of the sample's lateral dimensions. A linear mass diffusion model has been proposed to predict and explain the drying process of these ceramic colloidal suspensions. The calculated drying time is linearly proportional to the height of the slurry and the thickness of the negatively structured PDMS and is validated by the experimental results. An experimentally observed optimum Sylgard PDMS thickness range of ∼400 μm to 1 mm has achieved the best quality microstructured green compacts. Further, the model predicts that the drying time is independent of the microstructured areas and was validated using experimental observations carried out with microstructured areas of 300 mm(2), 1200 mm(2), and 120 cm(2). Therefore, in principle, the structures can be further replicated in areas up to 3 m(2) with the same drying time for the same slurry height. The surface-structured ceramics display interesting wetting properties, for example, eicosane-coated mesoporous microstructured alumina shows superhydrophobic behavior. Additionally, ceramic bulk samples could be further used as second-generation very hard and low-wear molds for further microfabrication.

iDBPs: a web server for the identification of DNA binding proteins

PubMed Central

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-01-01

Summary: The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. Availability: http://idbps.tau.ac.il/ Contact: NirB@tauex.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20089514

RNApdbee 2.0: multifunctional tool for RNA structure annotation.

PubMed

Zok, Tomasz; Antczak, Maciej; Zurkowski, Michal; Popenda, Mariusz; Blazewicz, Jacek; Adamiak, Ryszard W; Szachniuk, Marta

2018-04-30

In the field of RNA structural biology and bioinformatics, an access to correctly annotated RNA structure is of crucial importance, especially in the secondary and 3D structure predictions. RNApdbee webserver, introduced in 2014, primarily aimed to address the problem of RNA secondary structure extraction from the PDB files. Its new version, RNApdbee 2.0, is a highly advanced multifunctional tool for RNA structure annotation, revealing the relationship between RNA secondary and 3D structure given in the PDB or PDBx/mmCIF format. The upgraded version incorporates new algorithms for recognition and classification of high-ordered pseudoknots in large RNA structures. It allows analysis of isolated base pairs impact on RNA structure. It can visualize RNA secondary structures-including that of quadruplexes-with depiction of non-canonical interactions. It also annotates motifs to ease identification of stems, loops and single-stranded fragments in the input RNA structure. RNApdbee 2.0 is implemented as a publicly available webserver with an intuitive interface and can be freely accessed at http://rnapdbee.cs.put.poznan.pl/.

Electronic structure of Mott-insulator CaCu3Ti4O12: Photoemission and inverse photoemission study

NASA Astrophysics Data System (ADS)

Im, H. J.; Iwataki, M.; Yamazaki, S.; Usui, T.; Adachi, S.; Tsunekawa, M.; Watanabe, T.; Takegahara, K.; Kimura, S.; Matsunami, M.; Sato, H.; Namatame, H.; Taniguchi, M.

2015-09-01

We have performed the photoemission and inverse photoemission experiments to elucidate the origin of Mott insulating states in A-site ordered perovskite CaCu3Ti4O12 (CCTO). Experimental results have revealed that Cu 3d-O 2p hybridized bands, which are located around the Fermi level in the prediction of the local-density approximation (LDA) band calculations, are actually separated into the upper Hubbard band at ~1.5 eV and the lower Hubbard band at ~-1.7 eV with a band gap of ~1.5-1.8 eV. We also observed that Cu 3d peak at ~-3.8 eV and Ti 3d peak at ~3.8 eV are further away from each other than as indicated in the LDA calculations. In addition, it is found that the multiplet structure around -9 eV includes a considerable number of O 2p states. These observations indicate that the Cu 3d and Ti 3d electrons hybridized with the O 2p states are strongly correlated, which originates in the Mott-insulating states of CCTO.

Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K as anti-malarial agents

NASA Astrophysics Data System (ADS)

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-06-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents.

PubMed

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme ( Pf LDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The Pf LDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of Pf LDH, we have used Discovery studio to perform molecular docking in the active binding pocket of Pf LDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q 2 of 0.516. The model has predicted r 2 of 0.91 showing that predicted IC 50 values are in good agreement with experimental IC 50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents

PubMed Central

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors. PMID:28664157

Comparative 1D and 3D numerical investigation of open-channel junction flows and energy losses

NASA Astrophysics Data System (ADS)

Luo, Hao; Fytanidis, Dimitrios K.; Schmidt, Arthur R.; García, Marcelo H.

2018-07-01

The complexity of open channel confluences stems from flow mixing, secondary circulation, post-confluence flow separation, contraction and backwater effects. These effects in turn result in a large number of parameters required to adequately quantify the junction induced hydraulic resistance and describe mean flow pattern and turbulent flow structures due to flow merging. The recent development in computing power advances the application of 3D Computational Fluid Dynamics (CFD) codes to visualize and understand the Confluence Hydrodynamic Zone (CHZ). Nevertheless, 1D approaches remain the mainstay in large drainage network or waterway system modeling considering computational efficiency and data availability. This paper presents (i) a modified 1D nonlinear dynamic model; (ii) a fully 3D non-hydrostatic, Reynolds-averaged Navier-Stokes Equations (RANS)-based, Computational Fluid Dynamics (CFD) model; (iii) an analysis of changing confluence hydrodynamics and 3D turbulent flow structure under various controls; (iv) a comparison of flow features (i.e. upstream water depths, energy losses and post-confluence contraction) predicted by 1D and 3D models; and (v) parameterization of 3D flow characteristics in 1D modeling through the computation of correction coefficients associated with contraction, energy and momentum. The present comprehensive 3D numerical investigation highlights the driving mechanisms for junction induced energy losses. Moreover, the comparative 1D and 3D study quantifies the deviation of 1D approximations and associated underlying assumptions from the 'true' resultant flow field. The study may also shed light on improving the accuracy of the 1D large network modeling through the parameterization of the complex 3D feature of the flow field and correction of interior boundary conditions at junctions of larger angles and/or with substantial lateral inflows. Moreover, the enclosed numerical investigations may enhance the understanding of the primary mechanisms contributing to hydraulic structure induced turbulent flow behavior and increased hydraulic resistance.

Dual-spacecraft reconstruction of a three-dimensional magnetic flux rope at the Earth's magnetopause

DOE PAGES

Hasegawa, H.; Sonnerup, B. U. Ö.; Eriksson, S.; ...

2015-02-03

We present the first results of a data analysis method, developed by Sonnerup and Hasegawa (2011), for reconstructing three-dimensional (3-D), magnetohydrostatic structures from data taken as two closely spaced satellites traverse the structures. The method is applied to a magnetic flux transfer event (FTE), which was encountered on 27 June 2007 by at least three (TH-C, TH-D, and TH-E) of the five THEMIS probes near the subsolar magnetopause. The FTE was sandwiched between two oppositely directed reconnection jets under a southward interplanetary magnetic field condition, consistent with its generation by multiple X-line reconnection. The recovered 3-D field indicates that amore » magnetic flux rope with a diameter of ~ 3000 km was embedded in the magnetopause. The FTE flux rope had a significant 3-D structure, because the 3-D field reconstructed from the data from TH-C and TH-D (separated by ~ 390 km) better predicts magnetic field variations actually measured along the TH-E path than does the 2-D Grad–Shafranov reconstruction using the data from TH-C (which was closer to TH-E than TH-D and was at ~ 1250 km from TH-E). Such a 3-D nature suggests that the field lines reconnected at the two X-lines on both sides of the flux rope are entangled in a complicated way through their interaction with each other. The generation process of the observed 3-D flux rope is discussed on the basis of the reconstruction results and the pitch-angle distribution of electrons observed in and around the FTE.« less

D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies

NASA Astrophysics Data System (ADS)

Gaieb, Zied; Liu, Shuai; Gathiaka, Symon; Chiu, Michael; Yang, Huanwang; Shao, Chenghua; Feher, Victoria A.; Walters, W. Patrick; Kuhn, Bernd; Rudolph, Markus G.; Burley, Stephen K.; Gilson, Michael K.; Amaro, Rommie E.

2018-01-01

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.

Computational approach to analyze isolated ssDNA aptamers against angiotensin II.

PubMed

Heiat, Mohammad; Najafi, Ali; Ranjbar, Reza; Latifi, Ali Mohammad; Rasaee, Mohammad Javad

2016-07-20

Aptamers are oligonucleotides with highly structured molecules that can bind to their targets through specific 3-D conformation. Commonly, not all the nucleotides such as primer binding fixed region and some other sequences are vital for aptamers folding and interaction. Elimination of unnecessary regions needs trustworthy prediction tools to reduce experimental efforts and errors. Here we introduced a manipulated in-silico approach to predict the 3-D structure of aptamers and their target interactions. To design an approach for computational analysis of isolated ssDNA aptamers (FLC112, FLC125 and their truncated core region including CRC112 and CRC125), their secondary and tertiary structures were modeled by Mfold and RNA composer respectively. Output PDB files were modified from RNA to DNA in the discovery studio visualizer software. Using ZDOCK server, the aptamer-target interactions were predicted. Finally, the interaction scores were compared with the experimental results. In-silico interaction scores and the experimental outcomes were in the same descending arrangement of FLC112>CRC125>CRC112>FLC125 with similar intensity. The consistent results of innovative in-silico method with experimental outputs, affirmed that the present method may be a reliable approach. Also, it showed that the exact in-silico predictions can be utilized as a credible reference to find aptameric fragments binding potency. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting Student Performance in Sonographic Scanning Using Spatial Ability as an Ability Determinent of Skill Acquisition

ERIC Educational Resources Information Center

Clem, Douglas Wayne

2012-01-01

Spatial ability refers to an individual's capacity to visualize and mentally manipulate three dimensional objects. Since sonographers manually manipulate 2D and 3D sonographic images to generate multi-viewed, logical, sequential renderings of an anatomical structure, it can be assumed that spatial ability is central to the perception and…

Conformational organizations of G-quadruplexes composed of d(G(4)T(n))(3)G(4).

PubMed

Wong, Wan Chi; Zhuang, Jinyi; Ng, Selina Ling Ling; New, Lilian Li Lin; Hiew, Shuhui; Guo, Juanjuan; Yang, Zhaoqi; Li, Tianhu

2010-08-01

Structural polymorphism is one of the important issues with regard to G-quadruplexes because the structural diversity may significantly affect their biological functions in vivo and their physical property in nano-material. A series of oligonucleotides with four repeat guanines sequence [d(G(4)T(n))(3)G(4) (n=1-6)] were designed. In this study, the effects of loop length on the formation of structures of G-quadruplex were investigated through the result of CD (circular dichroism) and 20% non-denatured polyacrylamide gel electrophoresis. Our studies demonstrate that the length of loop in 100mM KCl solution could predict the conformation of G-quadruplex. Copyright 2010 Elsevier Ltd. All rights reserved.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016

NASA Astrophysics Data System (ADS)

Fradera, Xavier; Verras, Andreas; Hu, Yuan; Wang, Deping; Wang, Hongwu; Fells, James I.; Armacost, Kira A.; Crespo, Alejandro; Sherborne, Brad; Wang, Huijun; Peng, Zhengwei; Gao, Ying-Duo

2018-01-01

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.

Origin, distribution and 3D-modeling of Gr-EXPB1, an expansin from the potato cyst nematode Globodera rostochiensis.

PubMed

Kudla, Urszula; Qin, Ling; Milac, Adina; Kielak, Anna; Maissen, Cyril; Overmars, Hein; Popeijus, Herman; Roze, Erwin; Petrescu, Andrei; Smant, Geert; Bakker, Jaap; Helder, Johannes

2005-04-25

Southern analysis showed that Gr-EXPB1, a functional expansin from the potato cyst nematode Globodera rostochiensis, is member of a multigene family, and EST data suggest expansins to be present in other plant parasitic nematodes as well. Homology modeling predicted that Gr-EXPB1 domain 1 (D1) has a flat beta-barrel structure with surface-exposed aromatic rings, whereas the 3D structure of Gr-EXPB1-D2 was remarkably similar to plant expansins. Gr-EXPB1 shows highest sequence similarity to two extracellular proteins from saprophytic soil-inhabiting Actinobacteria, and includes a bacterial type II carbohydrate-binding module. These results support the hypothesis that a number of pathogenicity factors of cyst nematodes is of procaryotic origin and were acquired by horizontal gene transfer.

Microscale screening systems for 3D cellular microenvironments: platforms, advances, and challenges

PubMed Central

Montanez-Sauri, Sara I.; Beebe, David J.; Sung, Kyung Eun

2015-01-01

The increasing interest in studying cells using more in vivo-like three-dimensional (3D) microenvironments has created a need for advanced 3D screening platforms with enhanced functionalities and increased throughput. 3D screening platforms that better mimic in vivo microenvironments with enhanced throughput would provide more in-depth understanding of the complexity and heterogeneity of microenvironments. The platforms would also better predict the toxicity and efficacy of potential drugs in physiologically relevant conditions. Traditional 3D culture models (e.g. spinner flasks, gyratory rotation devices, non-adhesive surfaces, polymers) were developed to create 3D multicellular structures. However, these traditional systems require large volumes of reagents and cells, and are not compatible with high throughput screening (HTS) systems. Microscale technology offers the miniaturization of 3D cultures and allows efficient screening of various conditions. This review will discuss the development, most influential works, and current advantages and challenges of microscale culture systems for screening cells in 3D microenvironments. PMID:25274061

Effects of the enlargement of poly-glutamine segments on the structure and folding of ataxin-2 and ataxin-3 proteins

PubMed Central

Wen, Jingran; Scoles, Daniel R.; Facelli, Julio C.

2017-01-01

Spinocerebellar ataxia type 2 (SCA2) and type 3 (SCA3) are two common autosomal-dominant inherited ataxia syndromes, both of which are related to the unstable expansion of tri-nucleotide CAG repeats in the coding region of the related ATXN2 and ATXN3 genes, respectively. The poly-glutamine (poly-Q) tract encoded by the CAG repeats has long been recognized as an important factor in disease pathogenesis and progress. In this study, using the I-TASSER method for 3D structure prediction, we investigated the effect of poly-Q tract enlargement on the structure and folding of ataxin-2 and ataxin-3 proteins. Our results show good agreement with the known experimental structures of the Josephin and UIM domains providing credence to the simulation results presented here, which show that the enlargement of the poly-Q region not only affects the local structure of these regions but also affects the structures of functional domains as well as the whole protein. The changes observed in the predicted models of the UIM domains in ataxin-3 when the poly-Q track is enlarged provide new insights on possible pathogenic mechanisms. PMID:26861241

PIV Validation of 3D Multicomponent Model for Cold Spray Within Nitrogen and Helium Supersonic Flow Field

NASA Astrophysics Data System (ADS)

Faizan-Ur-Rab, M.; Zahiri, S. H.; Masood, S. H.; Jahedi, M.; Nagarajah, R.

2017-06-01

This study presents the validation of a developed three-dimensional multicomponent model for cold spray process using two particle image velocimetry (PIV) experiments. The k- ɛ type 3D model developed for spherical titanium particles was validated with the measured titanium particle velocity within a nitrogen and helium supersonic jet. The 3D model predicted lower values of particle velocity than the PIV experimental study that used irregularly shaped titanium particles. The results of the 3D model were consistent with the PIV experiment that used spherical titanium powder. The 3D model simulation of particle velocity within the helium and nitrogen jet was coupled with an estimation of titanium particle temperature. This was achieved with the consideration of the fact that cold spray particle temperature is difficult and expensive to measure due to considerably lower temperature of particles than thermal spray. The model predicted an interesting pattern of particle size distribution with respect to the location of impact with a concentration of finer particles close to the jet center. It is believed that the 3D model outcomes for particle velocity, temperature and location could be a useful tool to optimize system design, deposition process and mechanical properties of the additively manufactured cold spray structures.

Computational modeling of membrane proteins

PubMed Central

Leman, Julia Koehler; Ulmschneider, Martin B.; Gray, Jeffrey J.

2014-01-01

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefitted from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. PMID:25355688

Deconstructing three-dimensional (3D) structure of absorptive glass mat (AGM) separator to tailor pore dimensions and amplify electrolyte uptake

NASA Astrophysics Data System (ADS)

Rawal, Amit; Rao, P. V. Kameswara; Kumar, Vijay

2018-04-01

Absorptive glass mat (AGM) separator is a vital technical component in valve regulated lead acid (VRLA) batteries that can be tailored for a desired application. To selectively design and tailor the AGM separator, the intricate three-dimensional (3D) structure needs to be unraveled. Herein, a toolkit of 3D analytical models of pore size distribution and electrolyte uptake expressed via wicking characteristics of AGM separators under unconfined and confined states is presented. 3D data of fiber orientation distributions obtained previously through X-ray micro-computed tomography (microCT) analysis are used as key set of input parameters. The predictive ability of pore size distribution model is assessed through the commonly used experimental set-up that usually apply high level of compressive stresses. Further, the existing analytical model of wicking characteristics of AGM separators has been extended to account for 3D characteristics, and subsequently, compared with the experimental results. A good agreement between the theory and experiments pave the way to simulate the realistic charge-discharge modes of the battery by applying cyclic loading condition. A threshold criterion describing the invariant behavior of pore size and wicking characteristics in terms of maximum permissible limit of key structural parameters during charge-discharge mode of the battery has also been proposed.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents.

PubMed

Patel, Preeti; Singh, Avineesh; Patel, Vijay K; Jain, Deepak K; Veerasamy, Ravichandran; Rajak, Harish

2016-01-01

Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development. Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures. The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.

3D-QSAR and docking studies of 3-Pyridine heterocyclic derivatives as potent PI3K/mTOR inhibitors

NASA Astrophysics Data System (ADS)

Yang, Wenjuan; Shu, Mao; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Meng, Lingxin; Lin, Zhihua

2013-12-01

Phosphoinosmde-3-kinase/ mammalian target of rapamycin (PI3K/mTOR) dual inhibitors have attracted a great deal of interest as antitumor drugs research. In order to design and optimize these dual inhibitors, two types of 3D-quantitative structure-activity relationship (3D-QSAR) studies based on the ligand alignment and receptor alignment were applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). In the study based on ligands alignment, models of PI3K (CoMFA with r2, 0.770; q2, 0.622; CoMSIA with r2, 0.945; q2, 0.748) and mTOR (CoMFA with r2, 0.850; q2, 0.654; CoMSIA with r2, 0.983; q2, 0.676) have good predictability. And in the study based on receptor alignment, models of PI3K (CoMFA with r2, 0.745; q2, 0.538; CoMSIA with r2, 0.938; q2, 0.630) and mTOR (CoMFA with r2, 0.977; q2, 0.825; CoMSIA with r2, 0.985; q2, 0.728) also have good predictability. 3D contour maps and docking results suggested different groups on the core parts of the compounds could enhance the biological activities. Finally, ten derivatives as potential candidates of PI3K/mTOR inhibitors with good predicted activities were designed.

3D-Printed Tissue-Mimicking Phantoms for Medical Imaging and Computational Validation Applications

PubMed Central

Shahmirzadi, Danial; Li, Ronny X.; Doyle, Barry J.; Konofagou, Elisa E.; McGloughlin, Tim M.

2014-01-01

Abstract Abdominal aortic aneurysm (AAA) is a permanent, irreversible dilation of the distal region of the aorta. Recent efforts have focused on improved AAA screening and biomechanics-based failure prediction. Idealized and patient-specific AAA phantoms are often employed to validate numerical models and imaging modalities. To produce such phantoms, the investment casting process is frequently used, reconstructing the 3D vessel geometry from computed tomography patient scans. In this study the alternative use of 3D printing to produce phantoms is investigated. The mechanical properties of flexible 3D-printed materials are benchmarked against proven elastomers. We demonstrate the utility of this process with particular application to the emerging imaging modality of ultrasound-based pulse wave imaging, a noninvasive diagnostic methodology being developed to obtain regional vascular wall stiffness properties, differentiating normal and pathologic tissue in vivo. Phantom wall displacements under pulsatile loading conditions were observed, showing good correlation to fluid–structure interaction simulations and regions of peak wall stress predicted by finite element analysis. 3D-printed phantoms show a strong potential to improve medical imaging and computational analysis, potentially helping bridge the gap between experimental and clinical diagnostic tools. PMID:28804733

Automated body weight prediction of dairy cows using 3-dimensional vision.

PubMed

Song, X; Bokkers, E A M; van der Tol, P P J; Groot Koerkamp, P W G; van Mourik, S

2018-05-01

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

Shape forming by thermal expansion mismatch and shape memory locking in polymer/elastomer laminates

NASA Astrophysics Data System (ADS)

Yuan, Chao; Ding, Zhen; Wang, T. J.; Dunn, Martin L.; Qi, H. Jerry

2017-10-01

This paper studies a novel method to fabricate three-dimensional (3D) structure from 2D thermo-responsive shape memory polymer (SMP)/elastomer bilayer laminate. In this method, the shape change is actuated by the thermal mismatch strain between the SMP and the elastomer layers upon heating. However, the glass transition behavior of the SMP locks the material into a new 3D shape that is stable even upon cooling. Therefore, the second shape becomes a new permanent shape of the laminate. A theoretical model that accounts for the temperature-dependent thermomechanical behavior of the SMP material and thermal mismatch strain between the two layers is developed to better understand the underlying physics. Model predictions and experiments show good agreement and indicate that the theoretical model can well predict the bending behavior of the bilayer laminate. The model is then used in the optimal design of geometrical configuration and material selection. The latter also illustrates the requirement of thermomechanical behaviors of the SMP to lock the shape. Based on the fundamental understandings, several self-folding structures are demonstrated by the bilayer laminate design.

3D Structure of the Inverse Karman Vortex Street in the Wake of a Flapping Foil

NASA Astrophysics Data System (ADS)

Bozkurttas, Meliha; Mittal, Rajat; Dong, Haibo

2004-11-01

Flapping foils are being considered for lift generation and/or propulsion in Micro Aerial Vehicles (MAVs) and Autonomous Underwater Vehicles (AUVs). In the present study, a DNS/LES solver that is capable of simulating these flows in all their complexity will be used. The flow around a NACA 0012 foil undergoing pitch oscillation at a chord Reynolds number of 12600 has been investigated and the comparison of mean thrust coefficient results with the experiment has indicated significant under-prediction of the thrust although good match is observed with a 2D RANS calculation. This discrepancy could be related to the absence of 3D effects in both numerical simulations. Although this conclusion has also been reached in other studies, the details of the physical mechanism that lead to inaccurate prediction of surface pressure and ultimately to thrust force for pitching and heaving flapping foils have not been clarified yet. In this study, the streamwise (secondary) vortical structures in the inverse Karman Vortex Street generated in the wake of a thrust producing flapping foil will be studied.

Two aspartate residues at the putative p10 subunit of a type II metacaspase from Nicotiana tabacum L. may contribute to the substrate-binding pocket.

PubMed

Acosta-Maspons, Alexis; Sepúlveda-García, Edgar; Sánchez-Baldoquín, Laura; Marrero-Gutiérrez, Junier; Pons, Tirso; Rocha-Sosa, Mario; González, Lien

2014-01-01

Metacaspases are cysteine proteases present in plants, fungi, prokaryotes, and early branching eukaryotes, although a detailed description of their cellular function remains unclear. Currently, three-dimensional (3D) structures are only available for two metacaspases: Trypanosoma brucei (MCA2) and Saccharomyces cerevisiae (Yca1). Furthermore, metacaspases diverged from animal caspases of known structure, which limits straightforward homology-based interpretation of functional data. We report for the first time the identification and initial characterization of a metacaspase of Nicotiana tabacum L., NtMC1. By combining domain search, multiple sequence alignment (MSA), and protein fold-recognition studies, we provide compelling evidences that NtMC1 is a plant metacaspase type II, and predict its 3D structure using the crystal structure of two type I metacaspases (MCA2 and Yca1) and Gsu0716 protein from Geobacter sulfurreducens as template. Analysis of the predicted 3D structure allows us to propose Asp353, at the putative p10 subunit, as a new member of the aspartic acid triad that coordinates the P1 arginine/lysine residue of the substrate. Nevertheless, site-directed mutagenesis and expression analysis in bacteria and Nicotiana benthamiana indicate the functionality of both Asp348 and Asp353. Through the co-expression of mutant and wild-type proteins by transient expression in N. benthamiana leaves we found that polypeptide processing seems to be intramolecular. Our results provide the first evidence in plant metacaspases concerning the functionality of the putative p10 subunit.

Structure, ferroelectric ordering, and semiempirical quantum calculations of lanthanide based metal-organic framework: [Nd(C4H5O6)(C4H4O6)][3H2O

NASA Astrophysics Data System (ADS)

Ahmad, Bhat Zahoor; Want, Basharat

2016-04-01

We investigate the structure and ferroelectric behavior of a lanthanide based metal-organic framework (MOF), [Nd(C4H5O6)(C4H4O6)][3H2O]. X-ray crystal structure analyses reveal that it crystallizes in the P41212 space group with Nd centres, coordinated by nine oxygen atoms, forming a distorted capped square antiprismatic geometry. The molecules, bridged by tartrate ligands, form a 2D chiral structure. The 2D sheets are further linked into a 3D porous framework via strong hydrogen-bonding scheme (O-H…O ≈ 2.113 Å). Dielectric studies reveal two anomalies at 295 K and 185 K. The former is a paraelectric-ferroelectric transition, and the later is attributed to the freezing down of the motion of the hydroxyl groups. The phase transition is of second order, and the spontaneous polarization in low temperature phase is attributed to the ordering of protons of hydroxyl groups. The dielectric nonlinearity parameters have been calculated using Landau- Devonshire phenomenological theory. In addition, the most recent semiempirical models, Sparkle/PM7, Sparkle/RM1, and Sparkle/AM1, are tested on the present system to assay the accuracy of semiempirical quantum approaches to predict the geometries of solid MOFs. Our results show that Sparkle/PM7 model is the most accurate to predict the unit cell structure and coordination polyhedron geometry. The semiempirical methods are also used to calculate different ground state molecular properties.

An Enlisted Performance Prediction Model for Aviation Structural Mechanics.

DTIC Science & Technology

1983-09-01

D7- R136 784 RN ENLISTED PERFORMANCE PREDICTION MODEL FOR AVIATION 112 STRUCTURAL MECHANICS(U) NAVAL POSTGRADUATE SCHOOL MONTEREY CA R DWWHITMIRE ET...Selection 28 AESTRACT (C10000O 09OW1 @ewo o It 000041 .eewe 111Id f OF blook iubee0) ’The purpose of this thesis is to determine if the Navy’s system of...K ’Z-4 Dean of Info Policy Sciences 3 ABSTRACT The purpose of this thesis is to determine if the Navy’s system of assigning personnel to the

Disruption of Alfvénic turbulence by magnetic reconnection in a collisionless plasma

NASA Astrophysics Data System (ADS)

Mallet, Alfred; Schekochihin, Alexander A.; Chandran, Benjamin D. G.

2017-12-01

We calculate the disruption scale \\text{D}$ at which sheet-like structures in dynamically aligned Alfvénic turbulence are destroyed by the onset of magnetic reconnection in a low- collisionless plasma. The scaling of \\text{D}$ depends on the order of the statistics being considered, with more intense structures being disrupted at larger scales. The disruption scale for the structures that dominate the energy spectrum is \\text{D}\\sim L\\bot 1/9(de\\unicode[STIX]{x1D70C}s)4/9$ , where e$ is the electron inertial scale, s$ is the ion sound scale and \\bot $ is the outer scale of the turbulence. When e$ and s/L\\bot $ are sufficiently small, the scale \\text{D}$ is larger than s$ and there is a break in the energy spectrum at \\text{D}$ , rather than at s$ . We propose that the fluctuations produced by the disruption are circularised flux ropes, which may have already been observed in the solar wind. We predict the relationship between the amplitude and radius of these structures and quantify the importance of the disruption process to the cascade in terms of the filling fraction of undisrupted structures and the fractional reduction of the energy contained in them at the ion sound scale s$ . Both of these fractions depend strongly on e$ , with the disrupted structures becoming more important at lower e$ . Finally, we predict that the energy spectrum between \\text{D}$ and s$ is steeper than \\bot -3$ , when this range exists. Such a steep `transition range' is sometimes observed in short intervals of solar-wind turbulence. The onset of collisionless magnetic reconnection may therefore significantly affect the nature of plasma turbulence around the ion gyroscale.

Atom and receptor based 3D QSAR models for generating new conformations from pyrazolopyrimidine as IL-2 inducible tyrosine kinase inhibitors.

PubMed

Ul-Haq, Zaheer; Effendi, Juweria Shahrukh; Ashraf, Sajda; Bkhaitan, Majdi M

2017-06-01

In the current study, quantitative three-dimensional structure-activity-relationship (3D-QSAR) method was performed to design a model for new chemical entities by utilizing pyrazolopyrimidines. Their inhibiting activity on receptor IL-2 Itk correlates descriptors based on topology and hydrophobicity. The best model developed by ligand-based (atom-based) approach has correlation-coefficient of r 2 : 0.987 and cross-validated squared correlation-coefficient of q 2 : 0.541 with an external prediction capability of r 2 : 0.944. Whereas the best selected model developed by structured-based (receptor-based) approach has correlation-coefficient of r 2 : 0.987, cross-validated squared correlation-coefficient of q 2 : 0.637 with an external predictive ability of r 2 : 0.941. The statistical parameters prove that structure-based gave a better model to design new chemical scaffolds. The results achieved indicated that hydrophobicity at R 1 location play a vital role in the inhibitory activity and introduction of appropriately bulky and strongly hydrophobic-groups at position 3 of the terminal phenyl-group which is highly significant to enhance the activity. Six new pyrazolopyrimidine derivatives were designed. Docking simulation study was carried out and their inhibitory activity was predicted by the best structure based model with predictive activity of ranging from 8.43 to 8.85 log unit. The interacting residues PHE435, ASP500, LYS391, GLU436, MET438, CYS442, ILE369, VAL377 of PDB 4HCT were studied with respect to type of bonding with the new compounds. This study was aimed to search out more potent inhibitors of IL-2 Itk. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

PubMed

Méndez, Raúl; Leplae, Raphaël; Lensink, Marc F; Wodak, Shoshana J

2005-08-01

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.

Stability of the iterative solutions of integral equations as one phase freezing criterion.

PubMed

Fantoni, R; Pastore, G

2003-10-01

A recently proposed connection between the threshold for the stability of the iterative solution of integral equations for the pair correlation functions of a classical fluid and the structural instability of the corresponding real fluid is carefully analyzed. Direct calculation of the Lyapunov exponent of the standard iterative solution of hypernetted chain and Percus-Yevick integral equations for the one-dimensional (1D) hard rods fluid shows the same behavior observed in 3D systems. Since no phase transition is allowed in such 1D system, our analysis shows that the proposed one phase criterion, at least in this case, fails. We argue that the observed proximity between the numerical and the structural instability in 3D originates from the enhanced structure present in the fluid but, in view of the arbitrary dependence on the iteration scheme, it seems uneasy to relate the numerical stability analysis to a robust one-phase criterion for predicting a thermodynamic phase transition.

Structure of the Kπ=4+ bands in Os186,188

NASA Astrophysics Data System (ADS)

Phillips, A. A.; Garrett, P. E.; Lo Iudice, N.; Sushkov, A. V.; Bettermann, L.; Braun, N.; Burke, D. G.; Demand, G. A.; Faestermann, T.; Finlay, P.; Green, K. L.; Hertenberger, R.; Leach, K. G.; Krücken, R.; Schumaker, M. A.; Svensson, C. E.; Wirth, H.-F.; Wong, J.

2010-09-01

The (He3,d) single-proton stripping reaction has been performed on targets of Re185,187 to investigate the structures of the 43+ states in Os186,188. The experiment employed 30 MeV He3 beams, and the reaction products were analyzed with a Q3D spectrograph. Absolute cross sections were determined at nine angles between 5° and 50° for states up to approximately 3 MeV in excitation energy. Large (5)/(2)+[402]π+(3)/(2)+[402]π two-quasiparticle components are deduced for the 43+ levels of both isotopes. Their magnitudes are in agreement with calculations performed using the quasiparticle phonon model, which predicts a coexistence of a large hexadecapole with a smaller, but sizable, γ-γ component in the 43+.

Directing Matter: Toward Atomic-Scale 3D Nanofabrication

DOE PAGES

Jesse, Stephen; Borisevich, Albina Y.; Fowlkes, Jason D.; ...

2016-05-16

Here we report that enabling memristive, neuromorphic, and quantum based computing as well as efficient mainstream energy storage and conversion technologies requires next generation of materials customized at the atomic scale. This requires full control of atomic arrangement and bonding in three dimensions. The last two decades witnessed substantial industrial, academic, and government research efforts directed towards this goal through various lithographies and scanning probe based methods. These technologies emphasize 2D surface structures, with some limited 3D capability. Recently, a range of focused electron and ion based methods have demonstrated compelling alternative pathways to achieving atomically precise manufacturing of 3Dmore » structures in solids, liquids, and at interfaces. Electron and ion microscopies offer a platform that can simultaneously observe dynamic and static structures at the nano and atomic scales, and also induce structural rearrangements and chemical transformation. The addition of predictive modeling or rapid image analytics and feedback enables guiding these in a controlled manner. Here, we review the recent results that used focused electron and ion beams to create free-standing nanoscale 3D structures, radiolysis and the fabrication potential with liquid precursors, epitaxial crystallization of amorphous oxides with atomic layer precision, as well as visualization and control of individual dopant motion within a 3D crystal lattice. These works lay the foundation for new approaches to directing nanoscale level architectures and offer a potential roadmap to full 3D atomic control in materials. Lastly, in this perspective we lay out the gaps that currently constrain the processing range of these platforms, reflect on indirect requirements, such as the integration of large scale data analysis with theory, and discuss future prospects of these technologies.« less

RNA 3D Structural Motifs: Definition, Identification, Annotation, and Database Searching

NASA Astrophysics Data System (ADS)

Nasalean, Lorena; Stombaugh, Jesse; Zirbel, Craig L.; Leontis, Neocles B.

Structured RNA molecules resemble proteins in the hierarchical organization of their global structures, folding and broad range of functions. Structured RNAs are composed of recurrent modular motifs that play specific functional roles. Some motifs direct the folding of the RNA or stabilize the folded structure through tertiary interactions. Others bind ligands or proteins or catalyze chemical reactions. Therefore, it is desirable, starting from the RNA sequence, to be able to predict the locations of recurrent motifs in RNA molecules. Conversely, the potential occurrence of one or more known 3D RNA motifs may indicate that a genomic sequence codes for a structured RNA molecule. To identify known RNA structural motifs in new RNA sequences, precise structure-based definitions are needed that specify the core nucleotides of each motif and their conserved interactions. By comparing instances of each recurrent motif and applying base pair isosteriCity relations, one can identify neutral mutations that preserve its structure and function in the contexts in which it occurs.

Protein structure-structure alignment with discrete Fréchet distance.

PubMed

Jiang, Minghui; Xu, Ying; Zhu, Binhai

2008-02-01

Matching two geometric objects in two-dimensional (2D) and three-dimensional (3D) spaces is a central problem in computer vision, pattern recognition, and protein structure prediction. In particular, the problem of aligning two polygonal chains under translation and rotation to minimize their distance has been studied using various distance measures. It is well known that the Hausdorff distance is useful for matching two point sets, and that the Fréchet distance is a superior measure for matching two polygonal chains. The discrete Fréchet distance closely approximates the (continuous) Fréchet distance, and is a natural measure for the geometric similarity of the folded 3D structures of biomolecules such as proteins. In this paper, we present new algorithms for matching two polygonal chains in two dimensions to minimize their discrete Fréchet distance under translation and rotation, and an effective heuristic for matching two polygonal chains in three dimensions. We also describe our empirical results on the application of the discrete Fréchet distance to protein structure-structure alignment.

Does GaH5 exist?

NASA Astrophysics Data System (ADS)

Speakman, Lucas D.; Turney, Justin M.; Schaefer, Henry F.

2005-11-01

The existence or nonexistence of GaH5 has been widely discussed [N. M. Mitzel, Angew. Chem. Int. Ed. 42, 3856 (2003)]. Seven possible structures for gallium pentahydride have been systematically investigated using ab initio electronic structure theory. Structures and vibrational frequencies have been determined employing self-consistent field, coupled cluster including all single and double excitations (CCSD), and CCSD with perturbative triples levels of theory, with at least three correlation-consistent polarized-valence-(cc-pVXZ and aug-cc-pVXZ) type basis sets. The X˜A'1 state for GaH5 is predicted to be weakly bound complex 1 between gallane and molecular hydrogen, with Cs symmetry. The dissociation energy corresponding to GaH5→GaH3+H2 is predicted to be De=2.05kcalmol-1. The H-H stretching fundamental is predicted to be v =4060cm-1, compared to the tentatively assigned experimental feature of Wang and Andrews [J. Phys. Chem. A 107, 11371 (2003)] at 4087cm-1. A second Cs structure 2 with nearly equal energy is predicted to be a transition state, corresponding to a 90° rotation of the H2 bond. Thus the rotation of the hydrogen molecule is essentially free. However, hydrogen scrambling through the C2v structure 3 seems unlikely, as the activation barrier for scrambling is at least 30kcalmol-1 higher in energy than that for the dissociation of GaH5 to GaH3 and H2. Two additional structures consisting of GaH3 with a dihydrogen bond perpendicular to gallane (C3v structure 4) and an in-plane dihydrogen bond [Cs(III) structure 5] were also examined. A C3v symmetry second-order saddle point has nearly the same energy as the GaH3+H2 dissociation limit, while the Cs(III) structure 5 is a transition structure to the C3v structure. The C4v structure 6 and the D3h structure 7 are much higher in energy than GaH3+H2 by 88 and 103kcalmol-1, respectively.

Comparison of two LES codes for wind turbine wake studies

NASA Astrophysics Data System (ADS)

Sarlak, H.; Pierella, F.; Mikkelsen, R.; Sørensen, J. N.

2014-06-01

For the third time a blind test comparison in Norway 2013, was conducted comparing numerical simulations for the rotor Cp and Ct and wake profiles with the experimental results. As the only large eddy simulation study among participants, results of the Technical University of Denmark (DTU) using their in-house CFD solver, EllipSys3D, proved to be more reliable among the other models for capturing the wake profiles and the turbulence intensities downstream the turbine. It was therefore remarked in the workshop to investigate other LES codes to compare their performance with EllipSys3D. The aim of this paper is to investigate on two CFD solvers, the DTU's in-house code, EllipSys3D and the open-sourse toolbox, OpenFoam, for a set of actuator line based LES computations. Two types of simulations are performed: the wake behind a signle rotor and the wake behind a cluster of three inline rotors. Results are compared in terms of velocity deficit, turbulence kinetic energy and eddy viscosity. It is seen that both codes predict similar near-wake flow structures with the exception of OpenFoam's simulations without the subgrid-scale model. The differences begin to increase with increasing the distance from the upstream rotor. From the single rotor simulations, EllipSys3D is found to predict a slower wake recovery in the case of uniform laminar flow. From the 3-rotor computations, it is seen that the difference between the codes is smaller as the disturbance created by the downstream rotors causes break down of the wake structures and more homogenuous flow structures. It is finally observed that OpenFoam computations are more sensitive to the SGS models.

Considerations of the Use of 3-D Geophysical Models to Predict Test Ban Monitoring Observables

DTIC Science & Technology

2007-09-01

predict first P arrival times. Since this is a 3-D model, the travel times are predicted with a 3-D finite-difference code solving the eikonal equations...for the eikonal wave equation should provide more accurate predictions of travel-time from 3D models. These techniques and others are being

Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers

NASA Astrophysics Data System (ADS)

Mao, Yiqi; Yu, Kai; Isakov, Michael S.; Wu, Jiangtao; Dunn, Martin L.; Jerry Qi, H.

2015-09-01

Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

HSQC-TOCSY Fingerprinting-Directed Discovery of Antiplasmodial Polyketides from the Marine Ascidian-Derived Streptomyces sp. (USC-16018).

PubMed

Buedenbender, Larissa; Robertson, Luke P; Lucantoni, Leonardo; Avery, Vicky M; Kurtböke, D İpek; Carroll, Anthony R

2018-05-30

Chemical investigations on the fermentation extract obtained from an ascidian-derived Streptomyces sp. (USC-16018) yielded a new ansamycin polyketide, herbimycin G ( 1 ), as well as a known macrocyclic polyketide, elaiophylin ( 2 ), and four known diketopiperazines ( 3 ⁻ 6 ). The structures of the compounds were elucidated based on 1D/2D NMR and MS data. The absolute configuration of 1 was established by comparison of experimental and predicted electronic circular dichroism (ECD) data. Antiplasmodial activities were tested for the natural products against chloroquine sensitive (3D7) and chloroquine resistant (Dd2) Plasmodium falciparum strains; the two polyketides ( 1 ⁻ 2 ) demonstrated an inhibition of >75% against both parasite strains and while 2 was highly cytotoxic, herbimycin G ( 1 ) showed no cytotoxicity and good predicted water solubility.

TFaNS Tone Fan Noise Design/Prediction System. Volume 2; User's Manual; 1.4

NASA Technical Reports Server (NTRS)

Topol, David A.; Eversman, Walter

1999-01-01

TFaNS is the Tone Fan Noise Design/Prediction System developed by Pratt & Whitney under contract to NASA Lewis (presently NASA Glenn). The purpose of this system is to predict tone noise emanating from a fan stage including the effects of reflection and transmission by the rotor and stator and by the duct inlet and nozzle. These effects have been added to an existing annular duct/isolated stator noise prediction capability. TFaNS consists of: the codes that compute the acoustic properties (reflection and transmission coefficients) of the various elements and write them to files. CUP3D: Fan Noise Coupling Code that reads these files, solves the coupling problem, and outputs the desired noise predictions. AWAKEN: CFD/Measured Wake Postprocessor which reformats CFD wake predictions and/or measured wake data so it can be used by the system. This volume of the report provides information on code input and file structure essential for potential users of TFANS. This report is divided into three volumes: Volume 1. System Description, CUP3D Technical Documentation, and Manual for Code Developers; Volume 2. User's Manual, TFANS Vers. 1.4; Volume 3. Evaluation of System Codes.

Predicting a double mutant in the twilight zone of low homology modeling for the skeletal muscle voltage-gated sodium channel subunit beta-1 (Nav1.4 β1)

PubMed Central

Scior, Thomas; Paiz-Candia, Bertin; Islas, Ángel A.; Sánchez-Solano, Alfredo; Millan-Perez Peña, Lourdes; Mancilla-Simbro, Claudia; Salinas-Stefanon, Eduardo M.

2015-01-01

The molecular structure modeling of the β1 subunit of the skeletal muscle voltage-gated sodium channel (Nav1.4) was carried out in the twilight zone of very low homology. Structural significance can per se be confounded with random sequence similarities. Hence, we combined (i) not automated computational modeling of weakly homologous 3D templates, some with interfaces to analogous structures to the pore-bearing Nav1.4 α subunit with (ii) site-directed mutagenesis (SDM), as well as (iii) electrophysiological experiments to study the structure and function of the β1 subunit. Despite the distant phylogenic relationships, we found a 3D-template to identify two adjacent amino acids leading to the long-awaited loss of function (inactivation) of Nav1.4 channels. This mutant type (T109A, N110A, herein called TANA) was expressed and tested on cells of hamster ovary (CHO). The present electrophysiological results showed that the double alanine substitution TANA disrupted channel inactivation as if the β1 subunit would not be in complex with the α subunit. Exhaustive and unbiased sampling of “all β proteins” (Ig-like, Ig) resulted in a plethora of 3D templates which were compared to the target secondary structure prediction. The location of TANA was made possible thanks to another “all β protein” structure in complex with an irreversible bound protein as well as a reversible protein–protein interface (our “Rosetta Stone” effect). This finding coincides with our electrophysiological data (disrupted β1-like voltage dependence) and it is safe to utter that the Nav1.4 α/β1 interface is likely to be of reversible nature. PMID:25904995

Predicting a double mutant in the twilight zone of low homology modeling for the skeletal muscle voltage-gated sodium channel subunit beta-1 (Nav1.4 β1).

PubMed

Scior, Thomas; Paiz-Candia, Bertin; Islas, Ángel A; Sánchez-Solano, Alfredo; Millan-Perez Peña, Lourdes; Mancilla-Simbro, Claudia; Salinas-Stefanon, Eduardo M

2015-01-01

The molecular structure modeling of the β1 subunit of the skeletal muscle voltage-gated sodium channel (Nav1.4) was carried out in the twilight zone of very low homology. Structural significance can per se be confounded with random sequence similarities. Hence, we combined (i) not automated computational modeling of weakly homologous 3D templates, some with interfaces to analogous structures to the pore-bearing Nav1.4 α subunit with (ii) site-directed mutagenesis (SDM), as well as (iii) electrophysiological experiments to study the structure and function of the β1 subunit. Despite the distant phylogenic relationships, we found a 3D-template to identify two adjacent amino acids leading to the long-awaited loss of function (inactivation) of Nav1.4 channels. This mutant type (T109A, N110A, herein called TANA) was expressed and tested on cells of hamster ovary (CHO). The present electrophysiological results showed that the double alanine substitution TANA disrupted channel inactivation as if the β1 subunit would not be in complex with the α subunit. Exhaustive and unbiased sampling of "all β proteins" (Ig-like, Ig) resulted in a plethora of 3D templates which were compared to the target secondary structure prediction. The location of TANA was made possible thanks to another "all β protein" structure in complex with an irreversible bound protein as well as a reversible protein-protein interface (our "Rosetta Stone" effect). This finding coincides with our electrophysiological data (disrupted β1-like voltage dependence) and it is safe to utter that the Nav1.4 α/β1 interface is likely to be of reversible nature.

Improving consensus structure by eliminating averaging artifacts

PubMed Central

KC, Dukka B

2009-01-01

Background Common structural biology methods (i.e., NMR and molecular dynamics) often produce ensembles of molecular structures. Consequently, averaging of 3D coordinates of molecular structures (proteins and RNA) is a frequent approach to obtain a consensus structure that is representative of the ensemble. However, when the structures are averaged, artifacts can result in unrealistic local geometries, including unphysical bond lengths and angles. Results Herein, we describe a method to derive representative structures while limiting the number of artifacts. Our approach is based on a Monte Carlo simulation technique that drives a starting structure (an extended or a 'close-by' structure) towards the 'averaged structure' using a harmonic pseudo energy function. To assess the performance of the algorithm, we applied our approach to Cα models of 1364 proteins generated by the TASSER structure prediction algorithm. The average RMSD of the refined model from the native structure for the set becomes worse by a mere 0.08 Å compared to the average RMSD of the averaged structures from the native structure (3.28 Å for refined structures and 3.36 A for the averaged structures). However, the percentage of atoms involved in clashes is greatly reduced (from 63% to 1%); in fact, the majority of the refined proteins had zero clashes. Moreover, a small number (38) of refined structures resulted in lower RMSD to the native protein versus the averaged structure. Finally, compared to PULCHRA [1], our approach produces representative structure of similar RMSD quality, but with much fewer clashes. Conclusion The benchmarking results demonstrate that our approach for removing averaging artifacts can be very beneficial for the structural biology community. Furthermore, the same approach can be applied to almost any problem where averaging of 3D coordinates is performed. Namely, structure averaging is also commonly performed in RNA secondary prediction [2], which could also benefit from our approach. PMID:19267905

Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

PubMed

Zhan, Yiling; Guo, Shuyuan

2015-01-01

Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Shape: A 3D Modeling Tool for Astrophysics.

PubMed

Steffen, Wolfgang; Koning, Nicholas; Wenger, Stephan; Morisset, Christophe; Magnor, Marcus

2011-04-01

We present a flexible interactive 3D morpho-kinematical modeling application for astrophysics. Compared to other systems, our application reduces the restrictions on the physical assumptions, data type, and amount that is required for a reconstruction of an object's morphology. It is one of the first publicly available tools to apply interactive graphics to astrophysical modeling. The tool allows astrophysicists to provide a priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation. The tool has already been successfully used in a number of astrophysical research projects.

Terahertz laser vibration-rotation-tunneling spectrum of the water pentamer-d 10. . Constraints on the bifurcation tunneling dynamics

NASA Astrophysics Data System (ADS)

Cruzan, Jeff D.; Viant, Mark R.; Brown, Mac G.; Lucas, Don D.; Liu, Kun; Saykally, Richard J.

1998-08-01

The vibration-rotation-tunneling (VRT) spectrum of a low-frequency intermolecular vibration of (D 2O) 5 was recorded near 0.9 THz (30.2 cm -1). From an analysis of the relative intensities in the compact Q-branch region, the ground-state C-rotational constant is estimated to be 975±60 MHz, consistent with ab initio structural predictions. The precisely determined B-rotational constant ( B=1750.96±0.20 MHz) agrees well with previous results. Efforts to resolve possible bifurcation tunneling fine structure, such as that observed in VRT spectra of (D 2O) 3, revealed no such effects. This constrains the splittings to be less than 450 kHz, or roughly 3 times smaller than required by previous results.

Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces.

PubMed

Venselaar, Hanka; Te Beek, Tim A H; Kuipers, Remko K P; Hekkelman, Maarten L; Vriend, Gert

2010-11-08

Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background.

Micro-CT Characterization on the Meso-Structure of Three-Dimensional Full Five-Directional Braided Composite

NASA Astrophysics Data System (ADS)

Ya, Jixuan; Liu, Zhenguo; Wang, Yuanhang

2017-06-01

The meso-structure is important in predicting mechanical properties of the three-dimensional (3D) braided composite. In this paper, the internal structure and porosity of three-dimensional full five-directional (3DF5D) braided composite is characterized at mesoscopic scale (the scale of the yarns) using micro-computed tomography (micro-CT) non-destructively. Glass fiber yarns as tracer are added into the sample made of carbon fiber to enhance the contrast in the sectional images. The model of tracer yarns is established with 3D reconstruction method to analyze the cross-section and path of yarns. The porosities are reconstructed and characterized in the end. The results demonstrate that the cross sections of braiding yarns and axial yarns change with the regions and the heights in one pitch of 3DF5D braided composites. The path of braiding yarns are various in the different regions while the axial yarns are always straight. Helical indentations appear on the surfaces of the axial yarns because of the squeeze from braiding yarns. Moreover, the porosities in different shapes and sizes are almost located in the matrix and between the yarns.

Vibrational spectra and structure of benzil and its 18O- and d 10-labelled derivatives: a quantum chemical and experimental study

NASA Astrophysics Data System (ADS)

Kolev, Tsonko M.; Stamboliyska, Bistra A.

2002-12-01

Geometry and vibrational spectroscopic data of benzil-d 0 benzil-d 10 and benzil- 18O calculated at various levels of theory (RHF/6-31G*, B3LYP/6-31G*, BLYP/6-31G*) are reported. The theoretical results are discussed mainly in terms of the comparisons with infrared (4000-100 cm -1) and Raman (4000-50 cm -1) spectral data. The calculated isotopic frequency shifts, induced by the 18O- and d 10-labeling, are in a good agreement with the measured values. A complete vibrational assignment was made with the help of ab initio force field calculations. The data thus obtained were used for reassigning some vibrational frequencies. The results of the optimized molecular structure obtained on the basis of RHF and the DFT calculations are presented and compared with the experimental X-ray diffraction for the benzil-d 0 single crystal. It turns out that the best structural parameters are predicted by the B3LYP/6-31G* method.

Vibrational spectra and structure of benzil and its 18O- and d10-labelled derivatives: a quantum chemical and experimental study.

PubMed

Kolev, Tsonko M; Stamboliyska, Bistra A

2002-12-01

Geometry and vibrational spectroscopic data of benzil-d0 benzil-d10 and benzil-18O calculated at various levels of theory (RHF/6-31G*, B3LYP/6-31G*, BLYP/6-31G*) are reported. The theoretical results are discussed mainly in terms of the comparisons with infrared (4000-100 cm(-1)) and Raman (4000-50 cm(-1)) spectral data. The calculated isotopic frequency shifts, induced by the 18O- and d10-labeling, are in a good agreement with the measured values. A complete vibrational assignment was made with the help of ab initio force field calculations. The data thus obtained were used for reassigning some vibrational frequencies. The results of the optimized molecular structure obtained on the basis of RHF and the DFT calculations are presented and compared with the experimental X-ray diffraction for the benzil-d0 single crystal. It turns out that the best structural parameters are predicted by the B3LYP/6-31G* method.

Quantitative studies on structure-ORAC relationships of anthocyanins from eggplant and radish using 3D-QSAR.

PubMed

Jing, Pu; Zhao, Shujuan; Ruan, Siyu; Sui, Zhongquan; Chen, Lihong; Jiang, Linlei; Qian, Bingjun

2014-02-15

The 3-dimensional quantitative structure activity relationship (3D-QSAR) models were established from 21 anthocyanins based on their oxygen radical absorbing capacity (ORAC) and were applied to predict anthocyanins in eggplant and radish for their ORAC values. The cross-validated q(2)=0.857/0.729, non-cross-validated r(2) = 0.958/0.856, standard error of estimate = 0.153/0.134, and F = 73.267/19.247 were for the best QSAR (CoMFA/CoMSIA) models, where the correlation coefficient r(2)pred = 0.998/0.997 (>0.6) indicated a high predictive ability for each. Additionally, the contour map results suggested that structural characteristics of anthocyanins favourable for the high ORAC. Four anthocyanins from eggplant and radish have been screened based on the QSAR models. Pelargonidin-3-[(6''-p-coumaroyl)-glucosyl(2 → 1)glucoside]-5-(6''-malonyl)-glucoside, delphinidin-3-rutinoside-5-glucoside, and delphinidin-3-[(4''-p-coumaroyl)-rhamnosyl(1 → 6)glucoside]-5-glucoside potential with high ORAC based the QSAR models were isolated and also confirmed for their relative high antioxidant ability, which might attribute to the bulky and/or electron-donating substituent at the 3-position in the C ring or/and hydrogen bond donor group/electron donating group on the R1 position in the B ring. Copyright © 2013 Elsevier Ltd. All rights reserved.

2D SMARTCyp Reactivity-Based Site of Metabolism Prediction for Major Drug-Metabolizing Cytochrome P450 Enzymes

DTIC Science & Technology

2012-05-25

3. (A) X-ray structure of human CYP2C9 cocrystallized with flurbiprofen showing hydrogen bonding interactions between the anionic carboxyl group with...Figure 3 shows the X-ray crystal structure of human CYP2C9 cocrystallized with flurbiprofen . The structure indicates that the carboxyl group of... flurbiprofen forms hydrogen bonding interactions with the Arg108 and Asn204 side chains of the protein.35 Since the Arg108 and Asn204 side chains are at the

3D Protein structure prediction with genetic tabu search algorithm

PubMed Central

2010-01-01

Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively. PMID:20522256

3D-QSAR modeling and molecular docking studies on a series of 2,5 disubstituted 1,3,4-oxadiazoles

NASA Astrophysics Data System (ADS)

Ghaleb, Adib; Aouidate, Adnane; Ghamali, Mounir; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-10-01

3D-QSAR (comparative molecular field analysis (CoMFA)) and comparative molecular similarity indices analysis (CoMSIA) were performed on novel 2,5 disubstituted 1,3,4-oxadiazoles analogues as anti-fungal agents. The CoMFA and CoMSIA models using 13 compounds in the training set gives Q2 values of 0.52 and 0.51 respectively, while R2 values of 0.92. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to determine a three-dimensional quantitative structure-activity relationship. Based on this study a set of new molecules with high predicted activities were designed. Surflex-docking confirmed the stability of predicted molecules in the receptor.

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

Limb darkening laws for two exoplanet host stars derived from 3D stellar model atmospheres. Comparison with 1D models and HST light curve observations

NASA Astrophysics Data System (ADS)

Hayek, W.; Sing, D.; Pont, F.; Asplund, M.

2012-03-01

We compare limb darkening laws derived from 3D hydrodynamical model atmospheres and 1D hydrostatic MARCS models for the host stars of two well-studied transiting exoplanet systems, the late-type dwarfs HD 209458 and HD 189733. The surface brightness distribution of the stellar disks is calculated for a wide spectral range using 3D LTE spectrum formation and opacity sampling⋆. We test our theoretical predictions using least-squares fits of model light curves to wavelength-integrated primary eclipses that were observed with the Hubble Space Telescope (HST). The limb darkening law derived from the 3D model of HD 209458 in the spectral region between 2900 Å and 5700 Å produces significantly better fits to the HST data, removing systematic residuals that were previously observed for model light curves based on 1D limb darkening predictions. This difference arises mainly from the shallower mean temperature structure of the 3D model, which is a consequence of the explicit simulation of stellar surface granulation where 1D models need to rely on simplified recipes. In the case of HD 189733, the model atmospheres produce practically equivalent limb darkening curves between 2900 Å and 5700 Å, partly due to obstruction by spectral lines, and the data are not sufficient to distinguish between the light curves. We also analyze HST observations between 5350 Å and 10 500 Å for this star; the 3D model leads to a better fit compared to 1D limb darkening predictions. The significant improvement of fit quality for the HD 209458 system demonstrates the higher degree of realism of 3D hydrodynamical models and the importance of surface granulation for the formation of the atmospheric radiation field of late-type stars. This result agrees well with recent investigations of limb darkening in the solar continuum and other observational tests of the 3D models. The case of HD 189733 is no contradiction as the model light curves are less sensitive to the temperature stratification of the stellar atmosphere and the observed data in the 2900-5700 Å region are not sufficient to distinguish more clearly between the 3D and 1D limb darkening predictions. Full theoretical spectra for both stars are available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/539/A102, as well as at www.astro.ex.ac.uk/people/sing.

Active Structural Acoustic Control of Interior Noise on a Raytheon 1900D

NASA Technical Reports Server (NTRS)

Palumbo, Dan; Cabell, Ran; Sullivan, Brenda; Cline, John

2000-01-01

An active structural acoustic control system has been demonstrated on a Raytheon Aircraft Company 1900D turboprop airliner. Both single frequency and multi-frequency control of the blade passage frequency and its harmonics was accomplished. The control algorithm was a variant of the popular filtered-x LMS implemented in the principal component domain. The control system consisted of 21 inertial actuators and 32 microphones. The actuators were mounted to the aircraft's ring frames. The microphones were distributed uniformly throughout the interior at head height, both seated and standing. Actuator locations were selected using a combinatorial search optimization algorithm. The control system achieved a 14 dB noise reduction of the blade passage frequency during single frequency tests. Multi-frequency control of the first 1st, 2nd and 3rd harmonics resulted in 10.2 dB, 3.3 dB and 1.6 dB noise reductions respectively. These results fall short of the predictions which were produced by the optimization algorithm (13.5 dB, 8.6 dB and 6.3 dB). The optimization was based on actuator transfer functions taken on the ground and it is postulated that cabin pressurization at flight altitude was a factor in this discrepancy.

Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

USGS Publications Warehouse

Brien, Dianne L.; Reid, Mark E.

2008-01-01

In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

[Application and prospect of digital technology in the field of orthodontics].

PubMed

Zhou, Y H

2016-06-01

The three-dimensional(3D)digital technology has brought a revolutionary change in diagnostic planning and treatment strategy of orthodontics. Acquisition of 3D image data of the hard and soft tissues of the patients, diagnostic analysis and treatment prediction, and ultimately the individualized orthodontic appliance, will become the development trend and workflow of the 3D orthodontics. With the development of 3D digital technology, the traditional plaster model has been gradually replacing by 3D digital models. Meanwhile, 3D facial soft tissue scan and cone-beam CT scan have been gradually applied to clinical orthodontics, making it possible to get 3D virtual anatomical structure for patients. With the help of digital technology, the diagnostic process is much easier for orthodontist. However how to command the whole digital workflow and put it into practice in the daily work is still a long way to go. The purpose of this article is to enlighten the orthodontists interested in digital technology and discuss the future of digital orthodontics in China.

High-Fidelity 3D-Nanoprinting via Focused Electron Beams: Growth Fundamentals

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

Winkler, Robert; Lewis, Brett B.; Fowlkes, Jason Davidson

While 3D-printing is currently experiencing significant growth and having a significant impact on science and technology, the expansion into the nanoworld is still a highly challenging task. Among the increasing number of approaches, focused electron-beam-induced deposition (FEBID) was recently demonstrated to be a viable candidate toward a generic direct-write fabrication technology with spatial nanometer accuracy for complex shaped 3D-nanoarchitectures. In this comprehensive study, we explore the parameter space for 3D-FEBID and investigate the implications of individual and interdependent parameters on freestanding nanosegments, which act as a fundamental building block for complex 3D-structures. In particular, the study provides new basic insightsmore » such as precursor transport limitations and angle dependent growth rates, both essential for high-fidelity fabrication. In conclusion, complemented by practical aspects, we provide both basic insights in 3D-growth dynamics and technical guidance for specific process adaption to enable predictable and reliable direct-write synthesis of freestanding 3D-nanoarchitectures.« less

High-Fidelity 3D-Nanoprinting via Focused Electron Beams: Growth Fundamentals

DOE PAGES

Winkler, Robert; Lewis, Brett B.; Fowlkes, Jason Davidson; ...

2018-02-14

While 3D-printing is currently experiencing significant growth and having a significant impact on science and technology, the expansion into the nanoworld is still a highly challenging task. Among the increasing number of approaches, focused electron-beam-induced deposition (FEBID) was recently demonstrated to be a viable candidate toward a generic direct-write fabrication technology with spatial nanometer accuracy for complex shaped 3D-nanoarchitectures. In this comprehensive study, we explore the parameter space for 3D-FEBID and investigate the implications of individual and interdependent parameters on freestanding nanosegments, which act as a fundamental building block for complex 3D-structures. In particular, the study provides new basic insightsmore » such as precursor transport limitations and angle dependent growth rates, both essential for high-fidelity fabrication. In conclusion, complemented by practical aspects, we provide both basic insights in 3D-growth dynamics and technical guidance for specific process adaption to enable predictable and reliable direct-write synthesis of freestanding 3D-nanoarchitectures.« less

Prediction of global and local model quality in CASP8 using the ModFOLD server.

PubMed

McGuffin, Liam J

2009-01-01

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0--an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/. Copyright 2009 Wiley-Liss, Inc.

The discovery of novel histone lysine methyltransferase G9a inhibitors (part 1): molecular design based on a series of substituted 2,4-diamino-7- aminoalkoxyquinazoline by molecular-docking-guided 3D quantitative structure-activity relationship studies.

PubMed

Feng, Taotao; Wang, Hai; Zhang, Xiaojin; Sun, Haopeng; You, Qidong

2014-06-01

Protein lysine methyltransferase G9a, which catalyzes methylation of lysine 9 of histone H3 (H3K9) and lysine 373 (K373) of p53, is overexpressed in human cancers. This suggests that small molecular inhibitors of G9a might be attractive antitumor agents. Herein we report our efforts on the design of novel G9a inhibitor based on the 3D quantitative structure-activity relationship (3D-QSAR) analysis of a series of 2,4-diamino-7-aminoalkoxyquinazolineas G9a inhibitors. The 3D-QSAR model was generated from 47 compounds using docking based molecular alignment. The best predictions were obtained with CoMFA standard model (q2 =0.700, r2 = 0.952) and CoMSIA model combined with steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields (q2 = 0.724, r2 =0.960). The structural requirements for substituted 2,4-diamino-7-aminoalkoxyquinazoline for G9a inhibitory activity can be obtained by analysing the COMSIA plots. Based on the information, six novel follow-up analogs were designed.

An integrated geophysical study of the lithospheric structure beneath Libya

NASA Astrophysics Data System (ADS)

Brown, Wesley A.

This doctoral dissertation constitutes an integrated geophysical investigation of the lithospheric structure in the region of Libya. It is separated into three sections, each of which will be submitted to different scientific journals for publication. In the first part of the study, I utilized a seamless mosaicking approach based on the commercial Environment for Visualizing Images (ENVI) software package to create mosaics of two geologically interesting portions of Libya. In this study I present a step by step method of mosaicking Landsat 4 satellite images. Firstly, I performed histogram matching to give images the same color scale, then I used a cutline feathering technique to blend suture areas and finally I overlaid the images to form the two mosaics. The resulting mosaics were then combined with structural features and the seismicity map of the area. The resulting mosaics were proven to be useful in identifying recently active faults and shows great potential for verification of other faults and in natural hazard assessment. For the second portion of my research, I made use of over 6,000 free air corrected gravity data in conjunction with other geological and geophysical data to develop a 3D density model for northern Libya. I used a gravity modeling program (SURFGRAV) to develop the 3D density model by manipulating it to accurately predict large areas of Free Air anomaly shown in the data. The residual gravity anomaly values were calculated by subtracting predicted Free Air anomaly from the observed Free Air anomaly. The results were satisfactory for uplifted areas of Libya while there were significant mismatches in basin areas. The density model was iterated and used as a starting model for the final portion of the study. In the last part of this research, I used the Nafe-Drake relationship along with other geological data to convert the 3D density model to a 3D velocity model (LIBYA3D) for the region. Two earthquakes having source receiver paths sampling much of the modeled area were used to perform 1D and 1.5D validation tests, and the results were compared to those from previous studies. The results showed that the new 3D velocity model is valid and superior to the global model. However, until there is sufficient earthquake data acquired, and we are able to perform 2D and 3D modeling we may not be able to see the true improvement of LIBYA3D as compared to the other regional models.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

2016-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

3D Finite Element Analysis of Particle-Reinforced Aluminum

NASA Technical Reports Server (NTRS)

Shen, H.; Lissenden, C. J.

2002-01-01

Deformation in particle-reinforced aluminum has been simulated using three distinct types of finite element model: a three-dimensional repeating unit cell, a three-dimensional multi-particle model, and two-dimensional multi-particle models. The repeating unit cell model represents a fictitious periodic cubic array of particles. The 3D multi-particle (3D-MP) model represents randomly placed and oriented particles. The 2D generalized plane strain multi-particle models were obtained from planar sections through the 3D-MP model. These models were used to study the tensile macroscopic stress-strain response and the associated stress and strain distributions in an elastoplastic matrix. The results indicate that the 2D model having a particle area fraction equal to the particle representative volume fraction of the 3D models predicted the same macroscopic stress-strain response as the 3D models. However, there are fluctuations in the particle area fraction in a representative volume element. As expected, predictions from 2D models having different particle area fractions do not agree with predictions from 3D models. More importantly, it was found that the microscopic stress and strain distributions from the 2D models do not agree with those from the 3D-MP model. Specifically, the plastic strain distribution predicted by the 2D model is banded along lines inclined at 45 deg from the loading axis while the 3D model prediction is not. Additionally, the triaxial stress and maximum principal stress distributions predicted by 2D and 3D models do not agree. Thus, it appears necessary to use a multi-particle 3D model to accurately predict material responses that depend on local effects, such as strain-to-failure, fracture toughness, and fatigue life.

Perceptualization of geometry using intelligent haptic and visual sensing

NASA Astrophysics Data System (ADS)

Weng, Jianguang; Zhang, Hui

2013-01-01

We present a set of paradigms for investigating geometric structures using haptic and visual sensing. Our principal test cases include smoothly embedded geometry shapes such as knotted curves embedded in 3D and knotted surfaces in 4D, that contain massive intersections when projected to one lower dimension. One can exploit a touch-responsive 3D interactive probe to haptically override this conflicting evidence in the rendered images, by forcing continuity in the haptic representation to emphasize the true topology. In our work, we exploited a predictive haptic guidance, a "computer-simulated hand" with supplementary force suggestion, to support intelligent exploration of geometry shapes that will smooth and maximize the probability of recognition. The cognitive load can be reduced further when enabling an attention-driven visual sensing during the haptic exploration. Our methods combine to reveal the full richness of the haptic exploration of geometric structures, and to overcome the limitations of traditional 4D visualization.

Heritabilities of measured and mid-infrared predicted milk fat globule size, milk fat and protein percentages, and their genetic correlations.

PubMed

Fleming, A; Schenkel, F S; Koeck, A; Malchiodi, F; Ali, R A; Corredig, M; Mallard, B; Sargolzaei, M; Miglior, F

2017-05-01

The objective of this study was to estimate the heritability of milk fat globule (MFG) size and mid-infrared (MIR) predicted MFG size in Holstein cattle. The genetic correlations between measured and predicted MFG size with milk fat and protein percentage were also investigated. Average MFG size was measured in 1,583 milk samples taken from 254 Holstein cows from 29 herds across Canada. Size was expressed as volume moment mean (D[4,3]) and surface moment mean (D[3,2]). Analyzed milk samples also had average MFG size predicted from their MIR spectral records. Fat and protein percentages were obtained for all test-day milk samples in the cow's lactation. Univariate and bivariate repeatability animal models were used to estimate heritability and genetic correlations. Moderate heritabilities of 0.364 and 0.466 were found for D[4,3] and D[3,2], respectively, and a strong genetic correlation was found between the 2 traits (0.98). The heritabilities for the MIR-predicted MFG size were lower than those estimated for the measured MFG size at 0.300 for predicted D[4,3] and 0.239 for predicted D[3,2]. The genetic correlation between measured and predicted D[4,3] was 0.685; the correlation was slightly higher between measured and predicted D[3,2] at 0.764, likely due to the better prediction accuracy of D[3,2]. Milk fat percentage had moderate genetic correlations with both D[4,3] and D[3,2] (0.538 and 0.681, respectively). The genetic correlation between predicted MFG size and fat percentage was much stronger (greater than 0.97 for both predicted D[4,3] and D[3,2]). The stronger correlation suggests a limitation for the use of the predicted values of MFG size as indicator traits for true average MFG size in milk in selection programs. Larger samples sizes are required to provide better evidence of the estimated genetic parameters. A genetic component appears to exist for the average MFG size in bovine milk, and the variation could be exploited in selection programs. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Spectroscopy of the 1/2 2S → 3/2 2P transition in Yb ii: Isotope shifts, hyperfine splitting, and branching ratios

NASA Astrophysics Data System (ADS)

Feldker, T.; Fürst, H.; Ewald, N. V.; Joger, J.; Gerritsma, R.

2018-03-01

We report on spectroscopic results on the 1/2 2S → 3/2 2P transition in single trapped Yb+ ions. We measure the isotope shifts for all stable Yb+ isotopes except +173Yb, as well as the hyperfine splitting of the 3/2 2P state in +171Yb. Our results are in agreement with previous measurements but are a factor of 5-9 more precise. For the hyperfine constant A (3/2 2P)=875.4 (10 )MHz our results also agree with previous measurements but deviate significantly from theoretical predictions. We present experimental results on the branching ratios for the decay of the 3/2 2P state. We find branching fractions for the decay to the 3/2 2D state and 5/2 2D state of 0.17(1)% and 1.08(5)%, respectively, in rough agreement with theoretical predictions. Furthermore, we measured the isotope shifts of the 7/2 2F →1D[5/2 ] 5 /2 transition and determine the hyperfine structure constant for the 1D[5/2 ] 5 /2 state in +171Yb to be A (1D[5/2 ] 5 /2)=-107 (6 ) MHz .

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

Suenram, Richard D.; Pate, Brooks H.; Lesarri, Alberto

Twenty-five microwave lines were observed for cis-1,3,5-hexatriene (0.05 D dipole moment) and a smaller number for its three 13C isotopomers in natural abundance. Ground-state rotational constants were fitted for all four species to a Watson-type rotational Hamiltonian for an asymmetric top (κ ) -0.9768). Vibration-rotation (alpha) constants were predicted with a B3LYP/cc-pVTZ model and used to adjust the ground-state rotational constants to equilibrium rotational constants. The small inertial defect for cis-hexatriene shows that the molecule is planar, despite significant H-H repulsion. The substitution method was applied to the equilibrium rotational constants to give a semiexperimental equilibrium structure for the C6more » backbone. This structure and one predicted with the B3LYP/cc-pVTZ model show structural evidence for increased π-electron delocalization in comparison with butadiene, the first member of the polyene series.« less

Dual-Doppler lidar observation of horizontal convective rolls and near-surface streaks

NASA Astrophysics Data System (ADS)

Iwai, Hironori; Ishii, Shoken; Tsunematsu, Nobumitsu; Mizutani, Kohei; Murayama, Yasuhiro; Itabe, Toshikazu; Yamada, Izumi; Matayoshi, Naoki; Matsushima, Dai; Weiming, Sha; Yamazaki, Takeshi; Iwasaki, Toshiki

2008-07-01

Dual-Doppler lidar and heliborne sensors were used to investigate the three-dimensional (3D) structure of the wind field over Sendai Airport in June 2007. The 3D structures of several-hundred-meter-scale horizontal convective rolls (HCRs) in the sea-breeze layer were observed by the dual-Doppler lidar. The scale of the HCRs determined by the heliborne sensors roughly agreed with that determined by the dual-Doppler lidar. Analysis of the dual-Doppler lidar data showed that the region of upward flow in the HCRs originated in near-surface low-speed streaks. This structure is consistent with the results of large-eddy simulations of the atmospheric boundary layer. The aspect ratios of the HCRs were close to those predicted by linear theories.

Around the macrolide - Impact of 3D structure of macrocycles on lipophilicity and cellular accumulation.

PubMed

Koštrun, Sanja; Munic Kos, Vesna; Matanović Škugor, Maja; Palej Jakopović, Ivana; Malnar, Ivica; Dragojević, Snježana; Ralić, Jovica; Alihodžić, Sulejman

2017-06-16

The aim of this study was to investigate lipophilicity and cellular accumulation of rationally designed azithromycin and clarithromycin derivatives at the molecular level. The effect of substitution site and substituent properties on a global physico-chemical profile and cellular accumulation of investigated compounds was studied using calculated structural parameters as well as experimentally determined lipophilicity. In silico models based on the 3D structure of molecules were generated to investigate conformational effect on studied properties and to enable prediction of lipophilicity and cellular accumulation for this class of molecules based on non-empirical parameters. The applicability of developed models was explored on a validation and test sets and compared with previously developed empirical models. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Protein Tertiary Structure Prediction Based on Main Chain Angle Using a Hybrid Bees Colony Optimization Algorithm

NASA Astrophysics Data System (ADS)

Mahmood, Zakaria N.; Mahmuddin, Massudi; Mahmood, Mohammed Nooraldeen

Encoding proteins of amino acid sequence to predict classified into their respective families and subfamilies is important research area. However for a given protein, knowing the exact action whether hormonal, enzymatic, transmembranal or nuclear receptors does not depend solely on amino acid sequence but on the way the amino acid thread folds as well. This study provides a prototype system that able to predict a protein tertiary structure. Several methods are used to develop and evaluate the system to produce better accuracy in protein 3D structure prediction. The Bees Optimization algorithm which inspired from the honey bees food foraging method, is used in the searching phase. In this study, the experiment is conducted on short sequence proteins that have been used by the previous researches using well-known tools. The proposed approach shows a promising result.

Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

PubMed Central

Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

2014-01-01

This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

Towards large-scale mapping of urban three-dimensional structure using Landsat imagery and global elevation datasets

NASA Astrophysics Data System (ADS)

Wang, P.; Huang, C.

2017-12-01

The three-dimensional (3D) structure of buildings and infrastructures is fundamental to understanding and modelling of the impacts and challenges of urbanization in terms of energy use, carbon emissions, and earthquake vulnerabilities. However, spatially detailed maps of urban 3D structure have been scarce, particularly in fast-changing developing countries. We present here a novel methodology to map the volume of buildings and infrastructures at 30 meter resolution using a synergy of Landsat imagery and openly available global digital surface models (DSMs), including the Shuttle Radar Topography Mission (SRTM), ASTER Global Digital Elevation Map (GDEM), ALOS World 3D - 30m (AW3D30), and the recently released global DSM from the TanDEM-X mission. Our method builds on the concept of object-based height profile to extract height metrics from the DSMs and use a machine learning algorithm to predict height and volume from the height metrics. We have tested this algorithm in the entire England and assessed our result using Lidar measurements in 25 England cities. Our initial assessments achieved a RMSE of 1.4 m (R2 = 0.72) for building height and a RMSE of 1208.7 m3 (R2 = 0.69) for building volume, demonstrating the potential of large-scale applications and fully automated mapping of urban structure.

Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

PubMed

Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

2012-07-01

Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

High temperature breakdown of the Stokes-Einstein relation in a computer simulated Cu-Zr melt

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

Han, X. J., E-mail: xjhan@sjtu.edu.cn; Li, J. G., E-mail: lijg@sjtu.edu.cn; Schober, H. R., E-mail: h.schober@fz-juelich.de

Transport properties and the Stokes-Einstein (SE) relation in liquid Cu{sub 8}Zr{sub 3} are studied by molecular dynamics simulation with a modified embedded atom potential. The critical temperature T{sub c} of mode coupling theory (MCT) is derived as 930 K from the self-diffusion coefficient D and viscosity η. The SE relation breaks down around T{sub SE} = 1900 K, which is far above T{sub c}. At temperatures below T{sub SE}, the product of D and η fluctuates around a constant value, similar to the prediction of MCT near T{sub c}. The influence of the microscopic atomic motion on macroscopic properties ismore » investigated by analyzing the time dependent liquid structure and the self-hole filling process. The self-holes for the two components are preferentially filled by atoms of the same component. The self-hole filling dynamics explains the different breakdown behaviors of the SE relation in Zr-rich liquid CuZr{sub 2} compared to Cu-rich Cu{sub 8}Zr{sub 3}. At T{sub SE}, a kink is found in the temperature dependence of both partial and total coordination numbers for the three atomic pair combinations and of the typical time of self-hole filling. This indicates a strong correlation between liquid structure, atomic dynamics, and the breakdown of SE relation. The previously suggested usefulness of the parameter d(D{sub 1}/D{sub 2})/dT to predict T{sub SE} is confirmed. Additionally we propose a viscosity criterion to predict T{sub SE} in the absence of diffusion data.« less

Double valley Dirac fermions for 3D and 2D Hg1-x Cd x Te with strong asymmetry

NASA Astrophysics Data System (ADS)

Marchewka, M.

2017-04-01

In this paper the possibility to bring about the double-valley Dirac fermions in some quantum structures is predicted. These quantum structures are: strained 3D Hg1-x Cd x Te topological insulator (TI) with strong interface inversion asymmetry and the asymmetric Hg1-x Cd x Te double quantum wells (DQW). The numerical analysis of the dispersion relation for 3D TI Hg1-x Cd x Te for the proper Cd (x)-content of the Hg1-x Cd x Te compound clearly shows that the inversion symmetry breaking together with the unaxial tensile strain causes the splitting of each of the Dirac nodes (two belonging to two interfaces) into two in the proximity of the Γ-point. Similar effects can be obtained for asymmetric Hg1-x Cd x Te DQW with the proper content of Cd and proper width of the quantum wells. The aim of this work is to explore the inversion symmetry breaking in 3D TI and 2D DQW mixed HgCdTe systems. It is shown that this symmetry breaking leads to the dependence of carriers energy on quasi-momentum similar to that of Weyl fermions.

3D-QSAR study and design of 4-hydroxyamino α-pyranone carboxamide analogues as potential anti-HCV agents

NASA Astrophysics Data System (ADS)

Li, Wenlian; Xiao, Faqi; Zhou, Mingming; Jiang, Xuejin; Liu, Jun; Si, Hongzong; Xie, Meng; Ma, Xiuting; Duan, Yunbo; Zhai, Honglin

2016-09-01

The three dimensional-quantitative structure activity relationship (3D-QSAR) study was performed on a series of 4-hydroxyamino α-pyranone carboxamide analogues using comparative molecular similarity indices analysis (COMSIA). The purpose of the present study was to develop a satisfactory model providing a reliable prediction based on 4-hydroxyamino α-pyranone carboxamide analogues as anti-HCV (hepatitis C virus) inhibitors. The statistical results and the results of validation of this optimum COMSIA model were satisfactory. Furthermore, analysis of the contour maps helped to provide guidelines for finding structural requirement. Therefore, the satisfactory results from this study may provide useful guidelines for drug development of anti-HCV inhibitors.

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

Lu, Yuan; Zuo, Xu, E-mail: xzuo@nankai.edu.cn; Feng, Min

Motivated by recent theoretical predications for Dirac cone in two-dimensional (2D) triangular lattice [H. Ishizuka, Phys. Rev. Lett. 109, 237207 (2012)], first-principles studies are performed to predict Dirac cones in artificial structures of 3d transitional-metals (TM = Ti, V, Cr, Mn, Fe, Co, Ni, and Cu) doped Mg-Al spinels. In investigated artificial structures, TM dopants substitute specific positions of the B sub-lattice in Mg-Al spinel, and form a quasi-2D triangular lattice in the a-b plane. Calculated results illustrate the existence of the spin-polarized Dirac cones formed in d-wave bands at (around) the K-point in the momentum space. The study provides a promisingmore » route for engineering Dirac physics in condensed matters.« less

Anisotropic carrier mobility in single- and bi-layer C3N sheets

NASA Astrophysics Data System (ADS)

Wang, Xueyan; Li, Qingfang; Wang, Haifeng; Gao, Yan; Hou, Juan; Shao, Jianxin

2018-05-01

Based on the density functional theory combined with the Boltzmann transport equation with relaxation time approximation, we investigate the electronic structure and predict the carrier mobility of single- and bi-layer newly fabricated 2D carbon nitrides C3N. Although C3N sheets possess graphene-like planar hexagonal structure, the calculated carrier mobility is remarkably anisotropic, which is found mainly induced by the anisotropic effective masses and deformation potential constants. Importantly, we find that both the electron and hole mobilities are considerable high, for example, the hole mobility along the armchair direction of single-layer C3N sheets can arrive as high as 1.08 ×104 cm2 V-1 s-1, greatly larger than that of C2N-h2D and many other typical 2D materials. Owing to the high and anisotropic carrier mobility and appropriate band gap, single- and bi-layer semiconducting C3N sheets may have great potential applications in high performance electronic and optoelectronic devices.

Blasting Damage Predictions by Numerical Modeling in Siahbishe Pumped Storage Powerhouse

NASA Astrophysics Data System (ADS)

Eslami, Majid; Goshtasbi, Kamran

2018-04-01

One of the popular methods of underground and surface excavations is the use of blasting. Throughout this method of excavation, the loading resulted from blasting can be affected by different geo-mechanical and structural parameters of rock mass. Several factors affect turbulence in underground structures some of which are explosion, vibration, and stress impulses caused by the neighbouring blasting products. In investigating the blasting mechanism one should address the processes which expand with time and cause seismic events. To protect the adjoining structures against any probable deconstruction or damage, it is very important to model the blasting process prior to any actual operation. Efforts have been taken in the present study to demonstrate the potentiality of numerical methods in predicting the specified parameters in order to prevent any probable destruction. For this purpose the blasting process was modeled, according to its natural implementation, in one of the tunnels of Siahbishe dam by the 3DEC and AUTODYN 3D codes. 3DEC was used for modeling the blasting environment as well as the blast holes and AUTODYN 3D for modeling the explosion process in the blast hole. In this process the output of AUTODYN 3D, which is a result of modeling the blast hole and is in the form of stress waves, is entered into 3DEC. For analyzing the amount of destruction made by the blasting operation, the key parameter of Peak Particle Velocity was used. In the end, the numerical modeling results have been compared with the data recorded by the seismographs planted through the tunnel. As the results indicated 3DEC and AUTODYN 3D proved appropriate for analyzing such an issue. Therefore, by means of these two softwares one can analyze explosion processes prior to their implementation and make close estimation of the damage resulting from these processes.

Generalized thick strip modelling for vortex-induced vibration of long flexible cylinders

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

Bao, Y., E-mail: ybao@sjtu.edu.cn; Department of Aeronautics, Imperial College London, South Kensington Campus, London; Palacios, R., E-mail: r.palacios@imperial.ac.uk

2016-09-15

We propose a generalized strip modelling method that is computationally efficient for the VIV prediction of long flexible cylinders in three-dimensional incompressible flow. In order to overcome the shortcomings of conventional strip-theory-based 2D models, the fluid domain is divided into “thick” strips, which are sufficiently thick to locally resolve the small scale turbulence effects and three dimensionality of the flow around the cylinder. An attractive feature of the model is that we independently construct a three-dimensional scale resolving model for individual strips, which have local spanwise scale along the cylinder's axial direction and are only coupled through the structural modelmore » of the cylinder. Therefore, this approach is able to cover the full spectrum for fully resolved 3D modelling to 2D strip theory. The connection between these strips is achieved through the calculation of a tensioned beam equation, which is used to represent the dynamics of the flexible body. In the limit, however, a single “thick” strip would fill the full 3D domain. A parallel Fourier spectral/hp element method is employed to solve the 3D flow dynamics in the strip-domain, and then the VIV response prediction is achieved through the strip–structure interactions. Numerical tests on both laminar and turbulent flows as well as the comparison against the fully resolved DNS are presented to demonstrate the applicability of this approach.« less

3D Polarized Imaging of Coronal Mass Ejections: Chirality of a CME

NASA Astrophysics Data System (ADS)

DeForest, C. E.; de Koning, C. A.; Elliott, H. A.

2017-12-01

We report on a direct polarimetric determination of the chirality of a coronal mass ejection (CME), using the physics of Thomson scattering applied to synoptic polarized images from the Solar Terrestrial Relations Observatories/COR2 coronagraph. We confirmed the determination using in situ magnetic field measurements of the same CME with the ACE spacecraft. CME chirality is related to the helicity ejected from the solar corona along with the mass and field entrained in the CME. It is also important to prediction of the space-weather-relevant Z component of the CME magnetic field. Hence, remote measurement of CME chirality is an important step toward both understanding CME physics and predicting geoeffectiveness of individual CMEs. The polarimetric properties of Thomson scattering are well known and can, in principle, be used to measure the 3D structure of imaged objects in the solar corona and inner heliosphere. However, reduction of that principle to practice has been limited by the twin difficulties of background subtraction and the signal-to-noise ratio in coronagraph data. Useful measurements of the 3D structure require relative photometry at a few percent precision level in each linear polarization component of the K corona. This corresponds to a relative photometric precision of order 10-4 in direct images of the sky before subtraction of the F corona and related signal. Our measurement was enabled by recent developments in signal processing, which enable a better separation of the photometric signal from noise in the synoptic COR2 data. We discuss the relevance of this demonstration measurement to future instrument requirements, and to the future measurements of 3D structures in CMEs and other solar wind features.

Tailoring thermal conductivity via three-dimensional porous alumina

PubMed Central

Abad, Begoña; Maiz, Jon; Ruiz-Clavijo, Alejandra; Caballero-Calero, Olga; Martin-Gonzalez, Marisol

2016-01-01

Three-dimensional anodic alumina templates (3D-AAO) are an astonishing framework with open highly ordered three-dimensional skeleton structures. Since these templates are architecturally different from conventional solids or porous templates, they teem with opportunities for engineering thermal properties. By establishing the mechanisms of heat transfer in these frameworks, we aim to create materials with tailored thermal properties. The effective thermal conductivity of an empty 3D-AAO membrane was measured. As the effective medium theory was not valid to extract the skeletal thermal conductivity of 3D-AAO, a simple 3D thermal conduction model was developed, based on a mixed series and parallel thermal resistor circuit, giving a skeletal thermal conductivity value of approximately 1.25 W·m−1·K−1, which matches the value of the ordinary AAO membranes prepared from the same acid solution. The effect of different filler materials as well as the variation of the number of transversal nanochannels and the length of the 3D-AAO membrane in the effective thermal conductivity of the composite was studied. Finally, the thermal conductivity of two 3D-AAO membranes filled with cobalt and bismuth telluride was also measured, which was in good agreement with the thermal model predictions. Therefore, this work proved this structure as a powerful approach to tailor thermal properties. PMID:27934930

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

DFT and 3D-QSAR Studies of Anti-Cancer Agents m-(4-Morpholinoquinazolin-2-yl) Benzamide Derivatives for Novel Compounds Design

NASA Astrophysics Data System (ADS)

Zhao, Siqi; Zhang, Guanglong; Xia, Shuwei; Yu, Liangmin

2018-06-01

As a group of diversified frameworks, quinazolin derivatives displayed a broad field of biological functions, especially as anticancer. To investigate the quantitative structure-activity relationship, 3D-QSAR models were generated with 24 quinazolin scaffold molecules. The experimental and predicted pIC50 values for both training and test set compounds showed good correlation, which proved the robustness and reliability of the generated QSAR models. The most effective CoMFA and CoMSIA were obtained with correlation coefficient r 2 ncv of 1.00 (both) and leave-one-out coefficient q 2 of 0.61 and 0.59, respectively. The predictive abilities of CoMFA and CoMSIA were quite good with the predictive correlation coefficients ( r 2 pred ) of 0.97 and 0.91. In addition, the statistic results of CoMFA and CoMSIA were used to design new quinazolin molecules.

Strong ground motion prediction applying dynamic rupture simulations for Beppu-Haneyama Active Fault Zone, southwestern Japan

NASA Astrophysics Data System (ADS)

Yoshimi, M.; Matsushima, S.; Ando, R.; Miyake, H.; Imanishi, K.; Hayashida, T.; Takenaka, H.; Suzuki, H.; Matsuyama, H.

2017-12-01

We conducted strong ground motion prediction for the active Beppu-Haneyama Fault zone (BHFZ), Kyushu island, southwestern Japan. Since the BHFZ runs through Oita and Beppy cities, strong ground motion as well as fault displacement may affect much to the cities.We constructed a 3-dimensional velocity structure of a sedimentary basin, Beppu bay basin, where the fault zone runs through and Oita and Beppu cities are located. Minimum shear wave velocity of the 3d model is 500 m/s. Additional 1-d structure is modeled for sites with softer sediment: holocene plain area. We observed, collected, and compiled data obtained from microtremor surveys, ground motion observations, boreholes etc. phase velocity and H/V ratio. Finer structure of the Oita Plain is modeled, as 250m-mesh model, with empirical relation among N-value, lithology, depth and Vs, using borehole data, then validated with the phase velocity data obtained by the dense microtremor array observation (Yoshimi et al., 2016).Synthetic ground motion has been calculated with a hybrid technique composed of a stochastic Green's function method (for HF wave), a 3D finite difference (LF wave) and 1D amplification calculation. Fault geometry has been determined based on reflection surveys and active fault map. The rake angles are calculated with a dynamic rupture simulation considering three fault segments under a stress filed estimated from source mechanism of earthquakes around the faults (Ando et al., JpGU-AGU2017). Fault parameters such as the average stress drop, a size of asperity etc. are determined based on an empirical relation proposed by Irikura and Miyake (2001). As a result, strong ground motion stronger than 100 cm/s is predicted in the hanging wall side of the Oita plain.This work is supported by the Comprehensive Research on the Beppu-Haneyama Fault Zone funded by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Equilibrium reconstruction with 3D eddy currents in the Lithium Tokamak eXperiment

DOE PAGES

Hansen, C.; Boyle, D. P.; Schmitt, J. C.; ...

2017-04-18

Axisymmetric free-boundary equilibrium reconstructions of tokamak plasmas in the Lithium Tokamak eXperiment (LTX) are performed using the PSI-Tri equilibrium code. Reconstructions in LTX are complicated by the presence of long-lived non-axisymmetric eddy currents generated by a vacuum vessel and first wall structures. To account for this effect, reconstructions are performed with additional toroidal current sources in these conducting regions. The eddy current sources are fixed in their poloidal distributions, but their magnitude is adjusted as part of the full reconstruction. Eddy distributions are computed by toroidally averaging currents, generated by coupling to vacuum field coils, from a simplified 3D filamentmore » model of important conducting structures. The full 3D eddy current fields are also used to enable the inclusion of local magnetic field measurements, which have strong 3D eddy current pick-up, as reconstruction constraints. Using this method, equilibrium reconstruction yields good agreement with all available diagnostic signals. Here, an accompanying field perturbation produced by 3D eddy currents on the plasma surface with a primarily n = 2, m = 1 character is also predicted for these equilibria.« less

Pelton turbine Needle erosion prediction based on 3D three- phase flow simulation

NASA Astrophysics Data System (ADS)

Chongji, Z.; Yexiang, X.; Wei, Z.; Yangyang, Y.; Lei, C.; Zhengwei, W.

2014-03-01

Pelton turbine, which applied to the high water head and small flow rate, is widely used in the mountainous area. During the operation period the sediment contained in the water does not only induce the abrasion of the buckets, but also leads to the erosion at the nozzle which may damage the needle structure. The nozzle and needle structure are mainly used to form high quality cylindrical jet and increase the efficiency of energy exchange in the runner to the most. Thus the needle erosion will lead to the deformation of jet, and then may cause the efficiency loss and cavitation. The favourable prediction of abrasion characteristic of needle can effectively guide the optimization design and maintenance of needle structure. This paper simulated the unsteady three-dimensional multi-phase flow in the nozzle and injected jet flow. As the jet containing water and sediment is injected into the free atmosphere air with high velocity, the VOF model was adopted to predict the water and air flow. The sediment is simplified into round solid particle and the discrete particle model (DPM) was employed to predict the needle abrasion characteristic. The sand particle tracks were analyzed to interpret the mechanism of sand erosion on the needle surface. And the numerical result of needle abrasion was obtained and compared with the abrasion field observation. The similarity of abrasion pattern between the numerical results and field observation illustrated the validity of the 3D multi-phase flow simulation method.

Soft Computing Methods for Disulfide Connectivity Prediction.

PubMed

Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S

2015-01-01

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

Molecular design of new aggrecanases-2 inhibitors.

PubMed

Shan, Zhi Jie; Zhai, Hong Lin; Huang, Xiao Yan; Li, Li Na; Zhang, Xiao Yun

2013-10-01

Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications. Copyright © 2013 Elsevier Ltd. All rights reserved.

Parental artistic drawings of the fetus before and after 3-/4-dimensional ultrasonography.

PubMed

Pretorius, Dolores H; Hearon, Heather A; Hollenbach, Kathryn A; Ji, Eun-Kyung; Gattu, Shilpa; Nelson, Novella M; Nelson, Tanya M; Chibuk, Jason; Hull, Andrew D; Newton, Ruth P; Nelson, Thomas R

2007-03-01

The purpose of this study was to assess the impact of 3-/4-dimensional ultrasonography (3D/4DUS) on parental impressions of their fetus using preexamination and postexamination parental drawings. One hundred one parents (32 male and 69 female) were asked to draw pictures of their fetus immediately before and after undergoing 3D/4DUS. A drawing assessment instrument was used to evaluate the fetal anatomy by 4 reviewers. Overall descriptive quality and a comparison of before and after images were assessed. Reviewers judged the drawings as significantly different in 23% to 56% of cases, slightly different in 41% to 64%, and having no significant difference in 2% to 22%; some difference was identified in at least 78%. Reviewers familiar with ultrasonography were able to correctly predict which picture was drawn first in 78%. Differences identified were related to extremity positioning, personalized uterine environment, and artistic nature. No significant difference in the overall total scoring for anatomic differentiation before and after 3D/4DUS was found. A trend in drawing less anatomic structures after 3D/4DUS was discovered. Significantly fewer people drew hair after 3D/4DUS (P<.01) even when they had drawn hair before the 3D/4DUS. Similar significant differences were seen for the lower extremities (P<.01), with less detail being presented after the 3D/4DUS. Differences were seen between drawings made before and after 3D/4DUS by parents. Drawings after 3D/4DUS emphasized structures seen during the 3D/4DUS examination and were more reality based, whereas drawings before 3D/4DUS were more iconographic and based on preconceived anatomic knowledge.

Perceived crosstalk assessment on patterned retarder 3D display

NASA Astrophysics Data System (ADS)

Zou, Bochao; Liu, Yue; Huang, Yi; Wang, Yongtian

2014-03-01

CONTEXT: Nowadays, almost all stereoscopic displays suffer from crosstalk, which is one of the most dominant degradation factors of image quality and visual comfort for 3D display devices. To deal with such problems, it is worthy to quantify the amount of perceived crosstalk OBJECTIVE: Crosstalk measurements are usually based on some certain test patterns, but scene content effects are ignored. To evaluate the perceived crosstalk level for various scenes, subjective test may bring a more correct evaluation. However, it is a time consuming approach and is unsuitable for real­ time applications. Therefore, an objective metric that can reliably predict the perceived crosstalk is needed. A correct objective assessment of crosstalk for different scene contents would be beneficial to the development of crosstalk minimization and cancellation algorithms which could be used to bring a good quality of experience to viewers. METHOD: A patterned retarder 3D display is used to present 3D images in our experiment. By considering the mechanism of this kind of devices, an appropriate simulation of crosstalk is realized by image processing techniques to assign different values of crosstalk to each other between image pairs. It can be seen from the literature that the structures of scenes have a significant impact on the perceived crosstalk, so we first extract the differences of the structural information between original and distorted image pairs through Structural SIMilarity (SSIM) algorithm, which could directly evaluate the structural changes between two complex-structured signals. Then the structural changes of left view and right view are computed respectively and combined to an overall distortion map. Under 3D viewing condition, because of the added value of depth, the crosstalk of pop-out objects may be more perceptible. To model this effect, the depth map of a stereo pair is generated and the depth information is filtered by the distortion map. Moreover, human attention is one of important factors for crosstalk assessment due to the fact that when viewing 3D contents, perceptual salient regions are highly likely to be a major contributor to determining the quality of experience of 3D contents. To take this into account, perceptual significant regions are extracted, and a spatial pooling technique is used to combine structural distortion map, depth map and visual salience map together to predict the perceived crosstalk more precisely. To verify the performance of the proposed crosstalk assessment metric, subjective experiments are conducted with 24 participants viewing and rating 60 simuli (5 scenes * 4 crosstalk levels * 3 camera distances). After an outliers removal and statistical process, the correlation with subjective test is examined using Pearson and Spearman rank-order correlation coefficient. Furthermore, the proposed method is also compared with two traditional 2D metrics, PSNR and SSIM. The objective score is mapped to subjective scale using a nonlinear fitting function to directly evaluate the performance of the metric. RESULIS: After the above-mentioned processes, the evaluation results demonstrate that the proposed metric is highly correlated with the subjective score when compared with the existing approaches. Because the Pearson coefficient of the proposed metric is 90.3%, it is promising for objective evaluation of the perceived crosstalk. NOVELTY: The main goal of our paper is to introduce an objective metric for stereo crosstalk assessment. The novelty contributions are twofold. First, an appropriate simulation of crosstalk by considering the characteristics of patterned retarder 3D display is developed. Second, an objective crosstalk metric based on visual attention model is introduced.

PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

DTIC Science & Technology

2009-07-01

Evanseck JD, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 102...dimensional (3-D) protein structures are critical for the understanding of molecular mechanisms of living systems. Traditionally, X-ray crystallography...disordered proteins are often responsible for molecular recognition, molecular assembly, protein modifica- tion, and entropic chain activities in organisms [26

Identifying Future Scientists: Predicting Persistence into Research Training

PubMed Central

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8–12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers. PMID:18056303

Identifying future scientists: predicting persistence into research training.

PubMed

McGee, Richard; Keller, Jill L

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8-12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers.

Fold pattern formation in 3D

NASA Astrophysics Data System (ADS)

Schmid, Daniel W.; Dabrowski, Marcin; Krotkiewski, Marcin

2010-05-01

The vast majority of studies concerned with folding focus on 2D and assume that the resulting fold structures are cylindrically extended in the out of place direction. This simplification is often justified as fold aspect ratios, length/width, are quite large. However, folds always exhibit finite aspect ratios and it is unclear what controls this (cf. Fletcher 1995). Surprisingly little is known about the fold pattern formation in 3D for different in-plane loading conditions. Even more complicated is the pattern formation when several folding events are superposed. Let us take the example of a plane strain pure shear superposed by the same kind of deformation but rotated by 90 degrees. The text book prediction for this event is the formation of an egg carton structure; relevant analogue models either agree and produce type 1 interference patterns or contradict and produce type 2. In order to map out 3D fold pattern formation we have performed a systematic parameter space investigation using BILAMIN, our efficient unstructured mesh finite element Stokes solver. BILAMIN is capable of solving problems with more than half a billion unknowns. This allows us to study fold patterns that emerge in randomly (red noise) perturbed layers. We classify the resulting structures with differential geometry tools. Our results show that there is a relationship between fold aspect ratio and in-plane loading conditions. We propose that this finding can be used to determine the complete parameter set potentially contained in the geometry of three dimensional folds: mechanical properties of natural rocks, maximum strain, and relative strength of the in-plane far-field load components. Furthermore, we show how folds in 3D amplify and that there is a second deformation mode, besides continuous amplification, where compression leads to a lateral rearrangement of blocks of folds. Finally, we demonstrate that the textbook prediction of egg carton shaped dome and basin structures resulting from folding instabilities in constriction is largely oversimplified. The fold patterns resulting in this setting are curved, elongated folds with random orientation. Reference Fletcher, R. C. 1995. 3-Dimensional Folding and Necking of a Power-Law Layer - Are Folds Cylindrical, and, If So, Do We Understand Why. Tectonophysics 147(1-4), 65-83.

Semiconducting transition metal oxides.

PubMed

Lany, Stephan

2015-07-22

Open shell transition metal oxides are usually described as Mott or charge transfer insulators, which are often viewed as being disparate from semiconductors. Based on the premise that the presence of a correlated gap and semiconductivity are not mutually exclusive, this work reviews electronic structure calculations on the binary 3d oxides, so to distill trends and design principles for semiconducting transition metal oxides. This class of materials possesses the potential for discovery, design, and development of novel functional semiconducting compounds, e.g. for energy applications. In order to place the 3d orbitals and the sp bands into an integrated picture, band structure calculations should treat both contributions on the same footing and, at the same time, account fully for electron correlation in the 3d shell. Fundamentally, this is a rather daunting task for electronic structure calculations, but quasi-particle energy calculations in GW approximation offer a viable approach for band structure predictions in these materials. Compared to conventional semiconductors, the inherent multivalent nature of transition metal cations is more likely to cause undesirable localization of electron or hole carriers. Therefore, a quantitative prediction of the carrier self-trapping energy is essential for the assessing the semiconducting properties and to determine whether the transport mechanism is a band-like large-polaron conduction or a small-polaron hopping conduction. An overview is given for the binary 3d oxides on how the hybridization between the 3d crystal field symmetries with the O-p orbitals of the ligands affects the effective masses and the likelihood of electron and hole self-trapping, identifying those situations where small masses and band-like conduction are more likely to be expected. The review concludes with an illustration of the implications of the increased electronic complexity of transition metal cations on the defect physics and doping, using as an example the diversity of possible atomic and magnetic configurations of the O vacancy in TiO(2), and the high levels of hole doping in Co(2)ZnO(4) due to a self-doping mechanism that originates from the multivalence of Co.

Structures and Nuclear Quadrupole Coupling Tensors of a Series of Chlorine-Containing Hydrocarbons

NASA Astrophysics Data System (ADS)

Dikkumbura, Asela S.; Webster, Erica R.; Dorris, Rachel E.; Peebles, Rebecca A.; Peebles, Sean A.; Seifert, Nathan A.; Pate, Brooks

2016-06-01

Rotational spectra for gauche-1,2-dichloroethane (12DCE), gauche-1-chloro-2-fluoroethane (1C2FE) and both anti- and gauche-2,3-dichloropropene (23DCP) have been observed using chirped-pulse Fourier-transform microwave (FTMW) spectroscopy in the 6-18 GHz region. Although the anti conformers for all three species are predicted to be more stable than the gauche forms, they are nonpolar (12DCE) or nearly nonpolar (predicted dipole components for anti-1C2FE: μ_a = 0.11 D, μ_b = 0.02 D and for anti-23DCP: μ_a = 0.25 D, μ_b = 0.02 D); nevertheless, it was also possible to observe and assign the spectrum of anti-23DCP. Assignments of parent spectra and 37Cl and 13C substituted isotopologues utilized predictions at the MP2/6-311++G(2d,2p) level and Pickett's SPCAT/SPFIT programs. For the weak anti-23DCP spectra, additional measurements also utilized a resonant-cavity FTMW spectrometer. Full chlorine nuclear quadrupole coupling tensors for gauche-12DCE and both anti- and gauche-23DCP have been diagonalized to allow comparison of coupling constants. Kraitchman's equations were used to determine r_s coordinates of isotopically substituted atoms and r_0 structures were also deduced for gauche conformers of 12DCE and 1C2FE. Structural details and chlorine nuclear quadrupole coupling constants of all three molecules will be compared, and effects of differing halogen substitution and carbon chain length on molecular properties will be evaluated.

Predictive and comparative analysis of Ebolavirus proteins

PubMed Central

Cong, Qian; Pei, Jimin; Grishin, Nick V

2015-01-01

Ebolavirus is the pathogen for Ebola Hemorrhagic Fever (EHF). This disease exhibits a high fatality rate and has recently reached a historically epidemic proportion in West Africa. Out of the 5 known Ebolavirus species, only Reston ebolavirus has lost human pathogenicity, while retaining the ability to cause EHF in long-tailed macaque. Significant efforts have been spent to determine the three-dimensional (3D) structures of Ebolavirus proteins, to study their interaction with host proteins, and to identify the functional motifs in these viral proteins. Here, in light of these experimental results, we apply computational analysis to predict the 3D structures and functional sites for Ebolavirus protein domains with unknown structure, including a zinc-finger domain of VP30, the RNA-dependent RNA polymerase catalytic domain and a methyltransferase domain of protein L. In addition, we compare sequences of proteins that interact with Ebolavirus proteins from RESTV-resistant primates with those from RESTV-susceptible monkeys. The host proteins that interact with GP and VP35 show an elevated level of sequence divergence between the RESTV-resistant and RESTV-susceptible species, suggesting that they may be responsible for host specificity. Meanwhile, we detect variable positions in protein sequences that are likely associated with the loss of human pathogenicity in RESTV, map them onto the 3D structures and compare their positions to known functional sites. VP35 and VP30 are significantly enriched in these potential pathogenicity determinants and the clustering of such positions on the surfaces of VP35 and GP suggests possible uncharacterized interaction sites with host proteins that contribute to the virulence of Ebolavirus. PMID:26158395

Predictive and comparative analysis of Ebolavirus proteins.

PubMed

Cong, Qian; Pei, Jimin; Grishin, Nick V

2015-01-01

Ebolavirus is the pathogen for Ebola Hemorrhagic Fever (EHF). This disease exhibits a high fatality rate and has recently reached a historically epidemic proportion in West Africa. Out of the 5 known Ebolavirus species, only Reston ebolavirus has lost human pathogenicity, while retaining the ability to cause EHF in long-tailed macaque. Significant efforts have been spent to determine the three-dimensional (3D) structures of Ebolavirus proteins, to study their interaction with host proteins, and to identify the functional motifs in these viral proteins. Here, in light of these experimental results, we apply computational analysis to predict the 3D structures and functional sites for Ebolavirus protein domains with unknown structure, including a zinc-finger domain of VP30, the RNA-dependent RNA polymerase catalytic domain and a methyltransferase domain of protein L. In addition, we compare sequences of proteins that interact with Ebolavirus proteins from RESTV-resistant primates with those from RESTV-susceptible monkeys. The host proteins that interact with GP and VP35 show an elevated level of sequence divergence between the RESTV-resistant and RESTV-susceptible species, suggesting that they may be responsible for host specificity. Meanwhile, we detect variable positions in protein sequences that are likely associated with the loss of human pathogenicity in RESTV, map them onto the 3D structures and compare their positions to known functional sites. VP35 and VP30 are significantly enriched in these potential pathogenicity determinants and the clustering of such positions on the surfaces of VP35 and GP suggests possible uncharacterized interaction sites with host proteins that contribute to the virulence of Ebolavirus.

Quality assessment of protein model-structures based on structural and functional similarities.

PubMed

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models.

4D Origami by Smart Embroidery.

PubMed

Stoychev, Georgi; Razavi, Mir Jalil; Wang, Xianqiao; Ionov, Leonid

2017-09-01

There exist many methods for processing of materials: extrusion, injection molding, fibers spinning, 3D printing, to name a few. In most cases, materials with a static, fixed shape are produced. However, numerous advanced applications require customized elements with reconfigurable shape. The few available techniques capable of overcoming this problem are expensive and/or time-consuming. Here, the use of one of the most ancient technologies for structuring, embroidering, is proposed to generate sophisticated patterns of active materials, and, in this way, to achieve complex actuation. By combining experiments and computational modeling, the fundamental rules that can predict the folding behavior of sheets with a variety of stitch-patterns are elucidated. It is demonstrated that theoretical mechanics analysis is only suitable to predict the behavior of the simplest experimental setups, whereas computer modeling gives better predictions for more complex cases. Finally, the applicability of the rules by designing basic origami structures and wrinkling substrates with controlled thermal insulation properties is shown. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Surflex-Dock: Docking benchmarks and real-world application

NASA Astrophysics Data System (ADS)

Spitzer, Russell; Jain, Ajay N.

2012-06-01

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.

Advances in ultrasonic testing of austenitic stainless steel welds. Towards a 3D description of the material including attenuation and optimisation by inversion

NASA Astrophysics Data System (ADS)

Moysan, J.; Gueudré, C.; Ploix, M.-A.; Corneloup, G.; Guy, Ph.; Guerjouma, R. El; Chassignole, B.

In the case of multi-pass welds, the material is very difficult to describe due to its anisotropic and heterogeneous properties. Anisotropy results from the metal solidification and is correlated with the grain orientation. A precise description of the material is one of the key points to obtain reliable results with wave propagation codes. A first advance is the model MINA which predicts the grain orientations in multi-pass 316-L steel welds. For flat position welding, good predictions of the grains orientations were obtained using 2D modelling. In case of welding in position the resulting grain structure may be 3D oriented. We indicate how the MINA model can be improved for 3D description. A second advance is a good quantification of the attenuation. Precise measurements are obtained using plane waves angular spectrum method together with the computation of the transmission coefficients for triclinic material. With these two first advances, the third one is now possible: developing an inverse method to obtain the material description through ultrasonic measurements at different positions.

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

Flay, D.; Posik, M.; Parno, D. S.

We report on the results of the E06-014 experiment performed at Jefferson Lab in Hall A, where a precision measurement of the twist-3 matrix elementmore » $$d_2$$ of the neutron ($$d_{2}^{n}$$) was conducted. This quantity represents the average color Lorentz force a struck quark experiences in a deep inelastic electron scattering event off a neutron due to its interaction with the hadronizing remnants. This color force was determined from a linear combination of the third moments of the spin structure functions $$g_1$$ and $$g_2$$ on $$^{3}$$He after nuclear corrections had been applied to these moments. The kinematics included two average $$Q^{2}$$ bins of $3.2$ GeV$$^{2}$$ and $4.3$ GeV$$^{2}$$, and Bjorken-$x$ $$0.25 \\leq x \\leq 0.90$$ covering the DIS and resonance regions. We found $$d_2^n$$ to be small and negative for $ = 3.2$ GeV$$^{2}$$, and smaller for $ = 4.3$ GeV$$^{2}$$, consistent with a lattice QCD calculation. The twist-4 matrix element $$f_{2}^{n}$$ was extracted by combining our $$d_{2}^{n}$$ with the world data on $$\\Gamma_{1}^{n} = \\int_{0}^{1} g_{1}^{n} dx$$. We found $$f_{2}^{n}$$ to be roughly an order of magnitude larger than $$d_{2}^{n}$$. Utilizing the extracted $$d_{2}^{n}$$ and $$f_{2}^{n}$$ data, we separated the color force into its electric and magnetic components, $$F_{E}^{y,n}$$ and $$F_{B}^{y,n}$$, and found them to be equal and opposite in magnitude, in agreement with instanton model predictions but not with those from QCD sum rules. Additionally, we have extracted the neutron virtual photon-nucleon asymmetry $$A_{1}^{n}$$, the structure function ratio $$g_{1}^{n}/F_{1}^{n}$$, and the quark ratios $$(\\Delta u + \\Delta \\bar{u})/(u + \\bar{u})$$ and $$(\\Delta d + \\Delta \\bar{d})/(d + \\bar{d})$$. Lastly, these results were found to be consistent with DIS world data and with the prediction of the constituent quark model but at odds with those of perturbative QCD at large $x$.« less

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model.

PubMed

Kim, J; Lee, C; Chong, Y

2009-01-01

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q(2) = 0.763, r(2) = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.

Constructing and Validating 3D-pharmacophore Models to a Set of MMP-9 Inhibitors for Designing Novel Anti-melanoma Agents.

PubMed

Medeiros Turra, Kely; Pineda Rivelli, Diogo; Berlanga de Moraes Barros, Silvia; Mesquita Pasqualoto, Kerly Fernanda

2016-07-01

A receptor-independent (RI) four-dimensional structure-activity relationship (4D-QSAR) formalism was applied to a set of sixty-four β-N-biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP-9). MMP-9 belongs to a group of enzymes related to the cleavage of several extracellular matrix components and has been associated to cancer invasiveness/metastasis. The best RI 4D-QSAR model was statistically significant (N=47; r(2) =0.91; q(2) =0.83; LSE=0.09; LOF=0.35; outliers=0). Leave-N-out (LNO) and y-randomization approaches indicated the QSAR model was robust and presented no chance correlation, respectively. Furthermore, it also had good external predictability (82 %) regarding the test set (N=17). In addition, the grid cell occupancy descriptors (GCOD) of the predicted bioactive conformation for the most potent inhibitor were successfully interpreted when docked into the MMP-9 active site. The 3D-pharmacophore findings were used to predict novel ligands and exploit the MMP-9 calculated binding affinity through molecular docking procedure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural alignment of protein descriptors - a combinatorial model.

PubMed

Antczak, Maciej; Kasprzak, Marta; Lukasiak, Piotr; Blazewicz, Jacek

2016-09-17

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

Modification of polychlorinated phenols and evaluation of their toxicity, biodegradation and bioconcentration using three-dimensional quantitative structure-activity relationship models.

PubMed

Tong, Lidan; Guo, Lixin; Lv, Xiaojun; Li, Yu

2017-01-01

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were established by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Experimental toxicity data in Poecilia reticulata (pLC 50 ) and physico-chemical properties for 12 polychlorinated phenols were used as dependent and as independent variables, respectively. Among the 12 polychlorinated phenols, nine were randomly selected and used as a training set to construct the 3D-QSAR models through the SYBYL-X software to predict the pLC 50 values of the remaining 8 polychlorinated phenols congeners, and the other three polychlorinated phenols were used as a test set to evaluate the 3D-QSAR models (the training set and test set were arranged randomly, shuffled 60 times). Pentachlorophenol (PCP), which is the most toxic among the 20 polychlorinated phenols used in this experiment, was selected as an example for modification using contour maps produced using the established 3D-QSAR models. The aim was to decrease its toxicity and bioconcentration, increase its biodegradation, and maintain or better its effectiveness as a pesticide. The 3D-QSAR models were robust and had good predictive abilities with cross-validation correlation coefficients (q 2 ) of 0.858-0.992 (>0.5), correlation coefficients (r 2 ) of 0.966-1.000 (>0.9), and standard errors of prediction (SEP) of 0.004-0.159. CoMFA showed that the toxicity of the polychlorinated phenols arose mainly from electrostatic (42.7-66.7%) and steric (33.3-7.3%) contributions. By comparison, CoMSIA showed that the toxicity of polychlorinated phenols was dominated by electrostatic (57.5-76.9%) and hydrophobic (19.8-25.7%) contributions, with lesser contributions from the steric (0.7-1.0%) hydrogen bond donor (0.1-20.3%), and hydrogen bond acceptor (0-0.9%). 3D-QSAR electrostatic contour maps were used to modify PCP and design 11 new compounds with lower toxicity. The effectiveness of each of these molecules as a pesticide was verified using a 3D-QSAR model for polychlorinated phenol toxicity against Tetrahymena pyriformis. Four of these compounds, with -Br, -I, -OH and -NH 2 groups in place of chlorine at the 3-position on PCP, were all at least as effective as PCP against T. Pyriformis. The first-order rate constants (K b ) of these four compounds were predicted using a 3D-QSAR model for polychlorinated phenol degradation, which showed they were more biodegradable than PCP. Furthermore, a 3D-QSAR model for polychlorinated phenols bioconcentration in fish (containing Poecilia reticulata, Oncorhynchus mykiss, Pimephales promelas and Oryzias latipes) showed that there was no significant difference between the bioconcentration factors of the four new compounds and that of PCP. The results obtained are hoped to provide a new route for lowering the POPs characteristics of those polychlorinated phenol homologues and derivatives in use. Copyright © 2016 Elsevier Inc. All rights reserved.

Boundaries, mirror symmetry, and symplectic duality in 3d N = 4 gauge theory

DOE PAGES

Bullimore, Mathew; Dimofte, Tudor; Gaiotto, Davide; ...

2016-10-20

We introduce several families of N = (2, 2) UV boundary conditions in 3d N=4 gauge theories and study their IR images in sigma-models to the Higgs and Coulomb branches. In the presence of Omega deformations, a UV boundary condition defines a pair of modules for quantized algebras of chiral Higgs- and Coulomb-branch operators, respectively, whose structure we derive. In the case of abelian theories, we use the formalism of hyperplane arrangements to make our constructions very explicit, and construct a half-BPS interface that implements the action of 3d mirror symmetry on gauge theories and boundary conditions. Finally, by studyingmore » two-dimensional compactifications of 3d N = 4 gauge theories and their boundary conditions, we propose a physical origin for symplectic duality $-$ an equivalence of categories of modules associated to families of Higgs and Coulomb branches that has recently appeared in the mathematics literature, and generalizes classic results on Koszul duality in geometric representation theory. We make several predictions about the structure of symplectic duality, and identify Koszul duality as a special case of wall crossing.« less

The Prospect of using Three-Dimensional Earth Models To Improve Nuclear Explosion Monitoring and Ground Motion Hazard Assessment

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

Zucca, J J; Walter, W R; Rodgers, A J

2008-11-19

The last ten years have brought rapid growth in the development and use of three-dimensional (3D) seismic models of Earth structure at crustal, regional and global scales. In order to explore the potential for 3D seismic models to contribute to important societal applications, Lawrence Livermore National Laboratory (LLNL) hosted a 'Workshop on Multi-Resolution 3D Earth Models to Predict Key Observables in Seismic Monitoring and Related Fields' on June 6 and 7, 2007 in Berkeley, California. The workshop brought together academic, government and industry leaders in the research programs developing 3D seismic models and methods for the nuclear explosion monitoring andmore » seismic ground motion hazard communities. The workshop was designed to assess the current state of work in 3D seismology and to discuss a path forward for determining if and how 3D Earth models and techniques can be used to achieve measurable increases in our capabilities for monitoring underground nuclear explosions and characterizing seismic ground motion hazards. This paper highlights some of the presentations, issues, and discussions at the workshop and proposes two specific paths by which to begin quantifying the potential contribution of progressively refined 3D seismic models in critical applied arenas. Seismic monitoring agencies are tasked with detection, location, and characterization of seismic activity in near real time. In the case of nuclear explosion monitoring or seismic hazard, decisions to further investigate a suspect event or to launch disaster relief efforts may rely heavily on real-time analysis and results. Because these are weighty decisions, monitoring agencies are regularly called upon to meticulously document and justify every aspect of their monitoring system. In order to meet this level of scrutiny and maintain operational robustness requirements, only mature technologies are considered for operational monitoring systems, and operational technology necessarily lags contemporary research. Current monitoring practice is to use relatively simple Earth models that generally afford analytical prediction of seismic observables (see Examples of Current Monitoring Practice below). Empirical relationships or corrections to predictions are often used to account for unmodeled phenomena, such as the generation of S-waves from explosions or the effect of 3-dimensional Earth structure on wave propagation. This approach produces fast and accurate predictions in areas where empirical observations are available. However, accuracy may diminish away from empirical data. Further, much of the physics is wrapped into an empirical relationship or correction, which limits the ability to fully understand the physical processes underlying the seismic observation. Every generation of seismology researchers works toward quantitative results, with leaders who are active at or near the forefront of what has been computationally possible. While recognizing that only a 3-dimensional model can capture the full physics of seismic wave generation and propagation in the Earth, computational seismology has, until recently, been limited to simplifying model parameterizations (e.g. 1D Earth models) that lead to efficient algorithms. What is different today is the fact that the largest and fastest machines are at last capable of evaluating the effects of generalized 3D Earth structure, at levels of detail that improve significantly over past efforts, with potentially wide application. Advances in numerical methods to compute travel times and complete seismograms for 3D models are enabling new ways to interpret available data. This includes algorithms such as the Fast Marching Method (Rawlison and Sambridge, 2004) for travel time calculations and full waveform methods such as the spectral element method (SEM; Komatitsch et al., 2002, Tromp et al., 2005), higher order Galerkin methods (Kaser and Dumbser, 2006; Dumbser and Kaser, 2006) and advances in more traditional Cartesian finite difference methods (e.g. Pitarka, 1999; Nilsson et al., 2007). The ability to compute seismic observables using a 3D model is only half of the challenge; models must be developed that accurately represent true Earth structure. Indeed, advances in seismic imaging have followed improvements in 3D computing capability (e.g. Tromp et al., 2005; Rawlinson and Urvoy, 2006). Advances in seismic imaging methods have been fueled in part by theoretical developments and the introduction of novel approaches for combining different seismological observables, both of which can increase the sensitivity of observations to Earth structure. Examples of such developments are finite-frequency sensitivity kernels for body-wave tomography (e.g. Marquering et al., 1998; Montelli et al., 2004) and joint inversion of receiver functions and surface wave group velocities (e.g. Julia et al., 2000).« less

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Accuracy of three-dimensional soft tissue prediction for Le Fort I osteotomy using Dolphin 3D software: a pilot study.

PubMed

Resnick, C M; Dang, R R; Glick, S J; Padwa, B L

2017-03-01

Three-dimensional (3D) soft tissue prediction is replacing two-dimensional analysis in planning for orthognathic surgery. The accuracy of different computational models to predict soft tissue changes in 3D, however, is unclear. A retrospective pilot study was implemented to assess the accuracy of Dolphin 3D software in making these predictions. Seven patients who had a single-segment Le Fort I osteotomy and had preoperative (T 0 ) and >6-month postoperative (T 1 ) cone beam computed tomography (CBCT) scans and 3D photographs were included. The actual skeletal change was determined by subtracting the T 0 from the T 1 CBCT. 3D photographs were overlaid onto the T 0 CBCT and virtual skeletal movements equivalent to the achieved repositioning were applied using Dolphin 3D planner. A 3D soft tissue prediction (T P ) was generated and differences between the T P and T 1 images (error) were measured at 14 points and at the nasolabial angle. A mean linear prediction error of 2.91±2.16mm was found. The mean error at the nasolabial angle was 8.1±5.6°. In conclusion, the ability to accurately predict 3D soft tissue changes after Le Fort I osteotomy using Dolphin 3D software is limited. Copyright © 2016 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-04-01

Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q 2 of 0.578, R 2 of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 of 0.554, R 2 of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r 2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative structure-retention relationships of flavonoids unraveled by immobilized artificial membrane chromatography.

PubMed

Santoro, Adriana Leandra; Carrilho, Emanuel; Lanças, Fernando Mauro; Montanari, Carlos Alberto

2016-06-10

The pharmacokinetic properties of flavonoids with differing degrees of lipophilicity were investigated using immobilized artificial membranes (IAMs) as the stationary phase in high performance liquid chromatography (HPLC). For each flavonoid compound, we investigated whether the type of column used affected the correlation between the retention factors and the calculated octanol/water partition (log Poct). Three-dimensional (3D) molecular descriptors were calculated from the molecular structure of each compound using i) VolSurf software, ii) the GRID method (computational procedure for determining energetically favorable binding sites in molecules of known structure using a probe for calculating the 3D molecular interaction fields, between the probe and the molecule), and iii) the relationship between partition and molecular structure, analyzed in terms of physicochemical descriptors. The VolSurf built-in Caco-2 model was used to estimate compound permeability. The extent to which the datasets obtained from different columns differ both from each other and from both the calculated log Poct and the predicted permeability in Caco-2 cells was examined by principal component analysis (PCA). The immobilized membrane partition coefficients (kIAM) were analyzed using molecular descriptors in partial least square regression (PLS) and a quantitative structure-retention relationship was generated for the chromatographic retention in the cholesterol column. The cholesterol column provided the best correlation with the permeability predicted by the Caco-2 cell model and a good fit model with great prediction power was obtained for its retention data (R(2)=0.96 and Q(2)=0.85 with four latent variables). Copyright © 2015 Elsevier B.V. All rights reserved.

Validation of tautomeric and protomeric binding modes by free energy calculations. A case study for the structure based optimization of D-amino acid oxidase inhibitors.

PubMed

Orgován, Zoltán; Ferenczy, György G; Steinbrecher, Thomas; Szilágyi, Bence; Bajusz, Dávid; Keserű, György M

2018-02-01

Optimization of fragment size D-amino acid oxidase (DAAO) inhibitors was investigated using a combination of computational and experimental methods. Retrospective free energy perturbation (FEP) calculations were performed for benzo[d]isoxazole derivatives, a series of known inhibitors with two potential binding modes derived from X-ray structures of other DAAO inhibitors. The good agreement between experimental and computed binding free energies in only one of the hypothesized binding modes strongly support this bioactive conformation. Then, a series of 1-H-indazol-3-ol derivatives formerly not described as DAAO inhibitors was investigated. Binding geometries could be reliably identified by structural similarity to benzo[d]isoxazole and other well characterized series and FEP calculations were performed for several tautomers of the deprotonated and protonated compounds since all these forms are potentially present owing to the experimental pKa values of representative compounds in the series. Deprotonated compounds are proposed to be the most important bound species owing to the significantly better agreement between their calculated and measured affinities compared to the protonated forms. FEP calculations were also used for the prediction of the affinities of compounds not previously tested as DAAO inhibitors and for a comparative structure-activity relationship study of the benzo[d]isoxazole and indazole series. Selected indazole derivatives were synthesized and their measured binding affinity towards DAAO was in good agreement with FEP predictions.

Validation of tautomeric and protomeric binding modes by free energy calculations. A case study for the structure based optimization of d-amino acid oxidase inhibitors

NASA Astrophysics Data System (ADS)

Orgován, Zoltán; Ferenczy, György G.; Steinbrecher, Thomas; Szilágyi, Bence; Bajusz, Dávid; Keserű, György M.

2018-02-01

Optimization of fragment size d-amino acid oxidase (DAAO) inhibitors was investigated using a combination of computational and experimental methods. Retrospective free energy perturbation (FEP) calculations were performed for benzo[d]isoxazole derivatives, a series of known inhibitors with two potential binding modes derived from X-ray structures of other DAAO inhibitors. The good agreement between experimental and computed binding free energies in only one of the hypothesized binding modes strongly support this bioactive conformation. Then, a series of 1-H-indazol-3-ol derivatives formerly not described as DAAO inhibitors was investigated. Binding geometries could be reliably identified by structural similarity to benzo[d]isoxazole and other well characterized series and FEP calculations were performed for several tautomers of the deprotonated and protonated compounds since all these forms are potentially present owing to the experimental pKa values of representative compounds in the series. Deprotonated compounds are proposed to be the most important bound species owing to the significantly better agreement between their calculated and measured affinities compared to the protonated forms. FEP calculations were also used for the prediction of the affinities of compounds not previously tested as DAAO inhibitors and for a comparative structure-activity relationship study of the benzo[d]isoxazole and indazole series. Selected indazole derivatives were synthesized and their measured binding affinity towards DAAO was in good agreement with FEP predictions.

Real-time 3-D space numerical shake prediction for earthquake early warning

NASA Astrophysics Data System (ADS)

Wang, Tianyun; Jin, Xing; Huang, Yandan; Wei, Yongxiang

2017-12-01

In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake prediction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.

Elucidating the role of transcription in shaping the 3D structure of the bacterial genome

NASA Astrophysics Data System (ADS)

Brandao, Hugo B.; Wang, Xindan; Rudner, David Z.; Mirny, Leonid

Active transcription has been linked to several genome conformation changes in bacteria, including the recruitment of chromosomal DNA to the cell membrane and formation of nucleoid clusters. Using genomic and imaging data as input into mathematical models and polymer simulations, we sought to explore the extent to which bacterial 3D genome structure could be explained by 1D transcription tracks. Using B. subtilis as a model organism, we investigated via polymer simulations the role of loop extrusion and DNA super-coiling on the formation of interaction domains and other fine-scale features that are visible in chromosome conformation capture (Hi-C) data. We then explored the role of the condensin structural maintenance of chromosome complex on the alignment of chromosomal arms. A parameter-free transcription traffic model demonstrated that mean chromosomal arm alignment can be quantitatively explained, and the effects on arm alignment in genomically rearranged strains of B. subtilis were accurately predicted. H.B. acknowledges support from the Natural Sciences and Engineering Research Council of Canada for a PGS-D fellowship.

DockTrina: docking triangular protein trimers.

PubMed

Popov, Petr; Ritchie, David W; Grudinin, Sergei

2014-01-01

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein-protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three-dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair-wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair-wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano-d.inrialpes.fr/software/docktrina. Copyright © 2013 Wiley Periodicals, Inc.

Prediction of a two-dimensional S3N2 solid for optoelectronic applications

NASA Astrophysics Data System (ADS)

Xiao, Hang; Shi, Xiaoyang; Liao, Xiangbiao; Zhang, Yayun; Chen, Xi

2018-02-01

Two-dimensional materials have attracted tremendous attention for their fascinating electronic, optical, chemical, and mechanical properties. However, the band gaps of most reported two-dimensional (2D) materials are smaller than 2.0 eV, which has greatly restricted their optoelectronic applications in the blue and ultraviolet range of the spectrum. Here, we propose a stable trisulfur dinitride (S3N2 ) 2D crystal that is a covalent network composed solely of S-N σ bonds. The S3N2 crystal is dynamically, thermally, and chemically stable, as confirmed by the computed phonon spectrum and ab initio molecular dynamics simulations. GW calculations show that the S3N2 crystal is a wide, direct band-gap (3.92 eV) semiconductor with a small-hole effective mass. In addition, the band gap of S3N2 structures can be tuned by forming multilayer S3N2 crystals, S3N2 nanoribbons, and S3N2 nanotubes, expanding its potential applications. The anisotropic optical response of the 2D S3N2 crystal is revealed by GW-Bethe-Salpeter-equation calculations. The optical band gap of S3N2 is 2.73 eV and the exciton binding energy of S3N2 is 1.19 eV, showing a strong excitonic effect. Our result not only marks the prediction of a 2D crystal composed of nitrogen and sulfur, but also underpins potential innovations in 2D electronics and optoelectronics.

SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition.

PubMed

Wei, Ning-Ning; Hamza, Adel

2014-01-27

We present an efficient and rational ligand/structure shape-based virtual screening approach combining our previous ligand shape-based similarity SABRE (shape-approach-based routines enhanced) and the 3D shape of the receptor binding site. Our approach exploits the pharmacological preferences of a number of known active ligands to take advantage of the structural diversities and chemical similarities, using a linear combination of weighted molecular shape density. Furthermore, the algorithm generates a consensus molecular-shape pattern recognition that is used to filter and place the candidate structure into the binding pocket. The descriptor pool used to construct the consensus molecular-shape pattern consists of four dimensional (4D) fingerprints generated from the distribution of conformer states available to a molecule and the 3D shapes of a set of active ligands computed using SABRE software. The virtual screening efficiency of SABRE was validated using the Database of Useful Decoys (DUD) and the filtered version (WOMBAT) of 10 DUD targets. The ligand/structure shape-based similarity SABRE algorithm outperforms several other widely used virtual screening methods which uses the data fusion of multiscreening tools (2D and 3D fingerprints) and demonstrates a superior early retrieval rate of active compounds (EF(0.1%) = 69.0% and EF(1%) = 98.7%) from a large size of ligand database (∼95,000 structures). Therefore, our developed similarity approach can be of particular use for identifying active compounds that are similar to reference molecules and predicting activity against other targets (chemogenomics). An academic license of the SABRE program is available on request.

Computational molecular spectroscopy of X ˜ 2 Π NCS: Electronic properties and ro-vibrationally averaged structure

NASA Astrophysics Data System (ADS)

Hirano, Tsuneo; Nagashima, Umpei; Jensen, Per

2018-04-01

For NCS in the X ˜ 2 Π electronic ground state, three-dimensional potential energy surfaces (3D PESs) have been calculated ab initio at the core-valence, full-valence MR-SDCI+Q/[aug-cc-pCVQZ (N, C, S)] level of theory. The ab initio 3D PESs are employed in second-order-perturbation-theory and DVR3D calculations to obtain various molecular constants and ro-vibrationally averaged structures. The 3D PESs show that the X ˜ 2 Π NCS has its potential minimum at a linear configuration, and hence it is a "linear molecule." The equilibrium structure has re (N-C) = 1.1778 Å, re (C-S) = 1.6335 Å, and ∠e (N-C-S) = 180°. The ro-vibrationally averaged structure, determined as expectation values over DVR3D wavefunctions, has 〈 r (N-C)〉0 = 1.1836 Å, 〈 r (C-S)〉0 = 1.6356 Å, and 〈 ∠ (N-C-S)〉0 = 172.5°. Using these expectation values as the initial guess, a bent r0 structure having an 〈 ∠ (N-C-S)〉0 of 172.2° is deduced from the experimentally reported B0 values for NC32S and NC34S. Our previous prediction that a linear molecule, in any ro-vibrational state including the ro-vibrational ground state, is to be "observed" as being bent on ro-vibrational average, has been confirmed here theoretically through the expectation value for the bond-angle deviation from linearity, 〈 ρ bar 〉 , and experimentally through the interpretation of the experimentally derived rotational-constant values.

The approximate entropy concept extended to three dimensions for calibrated, single parameter structural complexity interrogation of volumetric images.

PubMed

Moore, Christopher; Marchant, Thomas

2017-07-12

Reconstructive volumetric imaging permeates medical practice because of its apparently clear depiction of anatomy. However, the tell tale signs of abnormality and its delineation for treatment demand experts work at the threshold of visibility for hints of structure. Hitherto, a suitable assistive metric that chimes with clinical experience has been absent. This paper develops the complexity measure approximate entropy (ApEn) from its 1D physiological origin into a three-dimensional (3D) algorithm to fill this gap. The first 3D algorithm for this is presented in detail. Validation results for known test arrays are followed by a comparison of fan-beam and cone-beam x-ray computed tomography image volumes used in image guided radiotherapy for cancer. Results show the structural detail down to individual voxel level, the strength of which is calibrated by the ApEn process itself. The potential for application in machine assisted manual interaction and automated image processing and interrogation, including radiomics associated with predictive outcome modeling, is discussed.

The approximate entropy concept extended to three dimensions for calibrated, single parameter structural complexity interrogation of volumetric images

NASA Astrophysics Data System (ADS)

Moore, Christopher; Marchant, Thomas

2017-08-01

Reconstructive volumetric imaging permeates medical practice because of its apparently clear depiction of anatomy. However, the tell tale signs of abnormality and its delineation for treatment demand experts work at the threshold of visibility for hints of structure. Hitherto, a suitable assistive metric that chimes with clinical experience has been absent. This paper develops the complexity measure approximate entropy (ApEn) from its 1D physiological origin into a three-dimensional (3D) algorithm to fill this gap. The first 3D algorithm for this is presented in detail. Validation results for known test arrays are followed by a comparison of fan-beam and cone-beam x-ray computed tomography image volumes used in image guided radiotherapy for cancer. Results show the structural detail down to individual voxel level, the strength of which is calibrated by the ApEn process itself. The potential for application in machine assisted manual interaction and automated image processing and interrogation, including radiomics associated with predictive outcome modeling, is discussed.

Predicting Organic Cation Sorption Coefficients: Accounting for Competition from Sorbed Inorganic Cations Using a Simple Probe Molecule.

PubMed

Jolin, William C; Goyetche, Reaha; Carter, Katherine; Medina, John; Vasudevan, Dharni; MacKay, Allison A

2017-06-06

With the increasing number of emerging contaminants that are cationic at environmentally relevant pH values, there is a need for robust predictive models of organic cation sorption coefficients (K d ). Current predictive models fail to account for the differences in the identity, abundance, and affinity of surface-associated inorganic exchange ions naturally present at negatively charged receptor sites on environmental solids. To better understand how organic cation sorption is influenced by surface-associated inorganic exchange ions, sorption coefficients of 10 organic cations (including eight pharmaceuticals and two simple probe organic amines) were determined for six homoionic forms of the aluminosilicate mineral, montmorillonite. Organic cation sorption coefficients exhibited consistent trends for all compounds across the various homoionic clays with sorption coefficients (K d ) decreasing as follows: K d Na + > K d NH 4 + ≥ K d K + > K d Ca 2+ ≥ K d Mg 2+ > K d Al 3+ . This trend for competition between organic cations and exchangeable inorganic cations is consistent with the inorganic cation selectivity sequence, determined for exchange between inorganic ions. Such consistent trends in competition between organic and inorganic cations suggested that a simple probe cation, such as phenyltrimethylammonium or benzylamine, could capture soil-to-soil variations in native inorganic cation identity and abundance for the prediction of organic cation sorption to soils and soil minerals. Indeed, sorption of two pharmaceutical compounds to 30 soils was better described by phenyltrimethylammonium sorption than by measures of benzylamine sorption, effective cation exchange capacity alone, or a model from the literature (Droge, S., and Goss, K. Environ. Sci. Technol. 2013, 47, 14224). A hybrid approach integrating structural scaling factors derived from this literature model of organic cation sorption, along with phenyltrimethylammonium K d values, allowed for estimation of K d values for more structurally complex organic cations to homoionic montmorillonites and to heteroionic soils (mean absolute error of 0.27 log unit). Accordingly, we concluded that the use of phenyltrimethylammonium as a probe compound was a promising means to account for the identity, affinity, and abundance of natural exchange ions in the prediction of organic cation sorption coefficients for environmental solids.

Direct ink writing of 3D conductive polyaniline structures and rheological modelling

NASA Astrophysics Data System (ADS)

Holness, F. Benjamin; Price, Aaron D.

2018-01-01

The intractable nature of conjugated polymers (CP) leads to practical limitations in the fabrication of CP-based transducers having complex three-dimensional geometries. Conventional CP device fabrication processes have focused primarily on thin-film deposition techniques; this study explores novel additive manufacturing processes specifically developed for CP with the ultimate goal of increasing the functionality of CP sensors and actuators. Herein we employ automated polymer paste extrusion processes for the direct ink writing of 3D conductive polyaniline (PANI) structures. Realization of these structures was enabled through a modified fused filament fabrication delta robot equipped with an integrated polymer paste extruder to fabricate high-resolution 3D conductive PANI structures. The required processability of PANI was achieved by means of a counterion-induced thermal doping method. The effect of thermal doping on the PANI-DBSA paste by means of a constitutive relationship to describe the paste flow as a function of the thermal doping time is explored. This relationship is incorporated within a flow model to predict the extruded track width as a function of various process parameters including: print speed, gauge pressure, nozzle diameter, and pre-extrusion thermal doping time.

GRIND2-based 3D-QSAR and prediction of activity spectra for symmetrical bis-pyridinium salts with promastigote antileishmanial activity.

PubMed

Diniz, Evelyn Mirella Lopes Pina; Tomich de Paula da Silva, Carlos Henrique; Gómez-Perez, Verónica; Federico, Leonardo Bruno; Campos Rosa, Joaquín María

2017-08-01

Leishmaniasis is a major group of neglected tropical diseases caused by the protozoan parasite Leishmania. About 12 million people are affected in 98 countries and 350 million people worldwide are at risk of infection. Current leishmaniasis treatments rely on a relatively small arsenal of drugs, including amphotericin B, pentamidine and others, which in general have some type of inconvenience. Recently, we have synthesized antileishmanial bis-pyridinium derivatives and symmetrical bis-pyridinium cyclophanes. These compounds are considered structural analogues of pentamidine, where the amidino moiety, protonated at physiological pH, is replaced by a positively charged nitrogen atom as a pyridinium ring. In this work, a statistically significant GRIND2-based 3D-QSAR model was built and biological activity predictions were in silico carried out allowing rationalization of the different activities recently obtained against Leishmania donovani (in L. donovani promastigotes) for a data set of 19 bis-pyridinium compounds. We will emphasize the most important structural requirements to improve the biological activity and probable interactions with the biological receptor as a guide for lead and prototype optimization. In addition, since no information about the actual biological target for this series of active compounds is provided, we have used Prediction of Activity Spectra for Biologically Active Substances to propose our compounds as potential nicotinic α6β3β4α5 receptor antagonists. This proposal is reinforced by the high structural similarity observed between our compounds and several anthelmintic drugs in current clinical use, which have the same drug action mechanism here predicted. Such new findings would be confirmed with further and additional experimental assays.

Computational chemistry calculations of stability for bismuth nanotubes, fullerene-like structures and hydrogen-containing nanostructures.

PubMed

Kharissova, Oxana V; Osorio, Mario; Vázquez, Mario Sánchez; Kharisov, Boris I

2012-08-01

Using molecular mechanics (MM+), semi-empirical (PM6) and density functional theory (DFT) (B3LYP) methods we characterized bismuth nanotubes. In addition, we predicted the bismuth clusters {Bi(20)(C(5V)), Bi(24)(C(6v)), Bi(28)(C(1)), B(32)(D(3H)), Bi(60)(C(I))} and calculated their conductor properties.

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

PubMed Central

2017-01-01

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal–organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groups into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure–energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy–structure–function maps. PMID:28776015

Interactions of ice sheet evolution, sea level and GIA in a region of complex Earth structure

NASA Astrophysics Data System (ADS)

Gomez, N. A.; Chan, N. H.; Latychev, K.; Pollard, D.; Powell, E. M.

2017-12-01

Constraining glacial isostatic adjustment (GIA) is challenging in Antarctica, where the solid Earth deformation, sea level changes and ice dynamics are strongly linked on all timescales. Furthermore, Earth structure beneath the Antarctic Ice Sheet is characterized by significant lateral variability. A stable, thick craton exists in the east, while the west is underlain by a large continental rift system, with a relatively thin lithosphere and hot, low viscosity asthenosphere, as indicated by high resolution seismic tomography. This implies that in parts of the West Antarctic, the Earth's mantle may respond to surface loading on shorter than average (centennial, or even decadal) timescales. Accounting for lateral variations in viscoelastic Earth structure alters the timing and geometry of load-induced Earth deformation, which in turn impacts the timing and extent of the ice-sheet retreat via a sea-level feedback, as well as predictions of relative sea-level change and GIA. We explore the impact of laterally varying Earth structure on ice-sheet evolution, sea level change and Earth deformation in the Antarctic region since the Last Glacial Maximum using a newly developed coupled ice sheet - sea level model that incorporates 3-D variations in lithospheric thickness and mantle viscosity derived from recent seismic tomographic datasets. Our results focus on identifying the regions and time periods in which the incorporation of 3-D Earth structure is critical for accurate predictions of ice sheet evolution and interpretation of geological and geodetic observations. We also investigate the sensitivity to the regional Earth structure of the relative contributions to modern GIA predictions of Last Deglacial and more recent Holocene ice cover changes.

Genetic analysis of PAX3 for diagnosis of Waardenburg syndrome type I.

PubMed

Matsunaga, Tatsuo; Mutai, Hideki; Namba, Kazunori; Morita, Noriko; Masuda, Sawako

2013-04-01

PAX3 genetic analysis increased the diagnostic accuracy for Waardenburg syndrome type I (WS1). Analysis of the three-dimensional (3D) structure of PAX3 helped verify the pathogenicity of a missense mutation, and multiple ligation-dependent probe amplification (MLPA) analysis of PAX3 increased the sensitivity of genetic diagnosis in patients with WS1. Clinical diagnosis of WS1 is often difficult in individual patients with isolated, mild, or non-specific symptoms. The objective of the present study was to facilitate the accurate diagnosis of WS1 through genetic analysis of PAX3 and to expand the spectrum of known PAX3 mutations. In two Japanese families with WS1, we conducted a clinical evaluation of symptoms and genetic analysis, which involved direct sequencing, MLPA analysis, quantitative PCR of PAX3, and analysis of the predicted 3D structure of PAX3. The normal-hearing control group comprised 92 subjects who had normal hearing according to pure tone audiometry. In one family, direct sequencing of PAX3 identified a heterozygous mutation, p.I59F. Analysis of PAX3 3D structures indicated that this mutation distorted the DNA-binding site of PAX3. In the other family, MLPA analysis and subsequent quantitative PCR detected a large, heterozygous deletion spanning 1759-2554 kb that eliminated 12-18 genes including a whole PAX3 gene.

Theory-Guided Synthesis of a Metastable Lead-Free Piezoelectric Polymorph.

PubMed

Garten, Lauren M; Dwaraknath, Shyam; Walker, Julian; Mangum, John S; Ndione, Paul F; Park, Yoonsang; Beaton, Daniel A; Gopalan, Venkatraman; Gorman, Brian P; Schelhas, Laura T; Toney, Michael F; Trolier-McKinstry, Susan; Persson, Kristin A; Ginley, David S

2018-05-10

Many technologically critical materials are metastable under ambient conditions, yet the understanding of how to rationally design and guide the synthesis of these materials is limited. This work presents an integrated approach that targets a metastable lead-free piezoelectric polymorph of SrHfO 3 . First-principles calculations predict that the previous experimentally unrealized, metastable P4mm phase of SrHfO 3 should exhibit a direct piezoelectric response (d 33 ) of 36.9 pC N -1 (compared to d 33 = 0 for the ground state). Combining computationally optimized substrate selection and synthesis conditions lead to the epitaxial stabilization of the polar P4mm phase of SrHfO 3 on SrTiO 3 . The films are structurally consistent with the theory predictions. A ferroelectric-induced large signal effective converse piezoelectric response of 5.2 pm V -1 for a 35 nm film is observed, indicating the ability to predict and target multifunctionality. This illustrates a coupled theory-experimental approach to the discovery and realization of new multifunctional polymorphs. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.