SOD activity of carboxyfullerenes predicts their neuroprotective efficacy: A structure-activity study

PubMed Central

Ali, Sameh Saad; Hardt, Joshua I.; Dugan, Laura L.

2008-01-01

Superoxide radical anion is a biologically important oxidant that has been linked to tissue injury and inflammation in several diseases. Here we carried out a structure-activity study on 6 different carboxyfullerene superoxide dismutase (SOD) mimetics with distinct electronic and biophysical characteristics. Neurotoxicity via NMDA receptors, which involves intracellular superoxide, was used as a model to evaluate structure-activity relationships between reactivity towards superoxide and neuronal rescue by these drugs. A significant correlation between neuroprotection by carboxyfullerenes and their ki towards superoxide radical was observed. Computer-assistant molecular modeling demonstrated that the reactivity towards superoxide is sensitive to changes in dipole moment which are dictated not only by the number of carboxyl groups, but also by their distribution on the fullerene ball. These results indicate that the SOD activity of these cell-permeable compounds predicts neuroprotection, and establishes a structure-activity relationship to aid in future studies on the biology of superoxide across disciplines. PMID:18656425

What is the effect of physical activity on the knee joint? A systematic review.

PubMed

Urquhart, Donna M; Tobing, Jephtah F L; Hanna, Fahad S; Berry, Patricia; Wluka, Anita E; Ding, Changhai; Cicuttini, Flavia M

2011-03-01

Although several studies have examined the relationship between physical activity and knee osteoarthritis, the effect of physical activity on knee joint health is unclear. The aim of this systematic review was to examine the relationships between physical activity and individual joint structures at the knee. Computer-aided searches were conducted up until November 2008, and the reference lists of key articles were examined. The methodological quality of selected studies was assessed based on established criteria, and a best-evidence synthesis was used to summarize the results. We found that the relationships between physical activity and individual joint structures at the knee differ. There was strong evidence for a positive association between physical activity and tibiofemoral osteophytes. However, we also found strong evidence for the absence of a relationship between physical activity and joint space narrowing, a surrogate method of assessing cartilage. Moreover, there was limited evidence from magnetic resonance imaging studies for a positive relationship between physical activity and cartilage volume and strong evidence for an inverse relationship between physical activity and cartilage defects. This systematic review found that knee structures are affected differently by physical activity. Although physical activity is associated with an increase in radiographic osteophytes, there was no related increase in joint space narrowing, rather emerging evidence of an associated increase in cartilage volume and decrease in cartilage defects on magnetic resonance imaging. Given that optimizing cartilage health is important in preventing osteoarthritis, these findings indicate that physical activity is beneficial, rather than detrimental, to joint health.

R-based Tool for a Pairwise Structure-activity Relationship Analysis.

PubMed

Klimenko, Kyrylo

2018-04-01

The Structure-Activity Relationship analysis is a complex process that can be enhanced by computational techniques. This article describes a simple tool for SAR analysis that has a graphic user interface and a flexible approach towards the input of molecular data. The application allows calculating molecular similarity represented by Tanimoto index & Euclid distance, as well as, determining activity cliffs by means of Structure-Activity Landscape Index. The calculation is performed in a pairwise manner either for the reference compound and other compounds or for all possible pairs in the data set. The results of SAR analysis are visualized using two types of plot. The application capability is demonstrated by the analysis of a set of COX2 inhibitors with respect to Isoxicam. This tool is available online: it includes manual and input file examples. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Medicinal Chemistry and Molecular Modeling: An Integration to Teach Drug Structure-Activity Relationship and the Molecular Basis of Drug Action

ERIC Educational Resources Information Center

Carvalho, Ivone; Borges, Aurea D. L.; Bernardes, Lilian S. C.

2005-01-01

The use of computational chemistry and the protein data bank (PDB) to understand and predict the chemical and molecular basis involved in the drug-receptor interactions is discussed. A geometrical and chemical overview of the great structural similarity in the substrate and inhibitor is provided.

The quantitative structure-insecticidal activity relationships from plant derived compounds against chikungunya and zika Aedes aegypti (Diptera:Culicidae) vector.

PubMed

Saavedra, Laura M; Romanelli, Gustavo P; Rozo, Ciro E; Duchowicz, Pablo R

2018-01-01

The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization. The present study constitutes a first necessary computational step for designing less toxic insecticides. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative structure activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives

NASA Astrophysics Data System (ADS)

Smith, P. J.; Popelier, P. L. A.

2004-02-01

The present day abundance of cheap computing power enables the use of quantum chemical ab initio data in Quantitative Structure-Activity Relationships (QSARs). Optimised bond lengths are a new such class of descriptors, which we have successfully used previously in representing electronic effects in medicinal and ecological QSARs (enzyme inhibitory activity, hydrolysis rate constants and pKas). Here we use AM1 and HF/3-21G* bond lengths in conjunction with Partial Least Squares (PLS) and a Genetic Algorithm (GA) to predict the Corticosteroid-Binding Globulin (CBG) binding activity of the classic steroid data set, and the antibacterial activity of nitrofuran derivatives. The current procedure, which does not require molecular alignment, produces good r2 and q2 values. Moreover, it highlights regions in the common steroid skeleton deemed relevant to the active regions of the steroids and nitrofuran derivatives.

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.

Progress in the Visualization and Mining of Chemical and Target Spaces.

PubMed

Medina-Franco, José L; Aguayo-Ortiz, Rodrigo

2013-12-01

Chemogenomics is a growing field that aims to integrate the chemical and target spaces. As part of a multi-disciplinary effort to achieve this goal, computational methods initially developed to visualize the chemical space of compound collections and mine single-target structure-activity relationships, are being adapted to visualize and mine complex relationships in chemogenomics data sets. Similarly, the growing evidence that clinical effects are many times due to the interaction of single or multiple drugs with multiple targets, is encouraging the development of novel methodologies that are integrated in multi-target drug discovery endeavors. Herein we review advances in the development and application of approaches to generate visual representations of chemical space with particular emphasis on methods that aim to explore and uncover relationships between chemical and target spaces. Also, progress in the data mining of the structure-activity relationships of sets of compounds screened across multiple targets are discussed in light of the concept of activity landscape modeling. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

PubMed

Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

2006-11-01

In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.

Computational design of a thermostable mutant of cocaine esterase via molecular dynamics simulations.

PubMed

Huang, Xiaoqin; Gao, Daquan; Zhan, Chang-Guo

2011-06-07

Cocaine esterase (CocE) has been known as the most efficient native enzyme for metabolizing naturally occurring cocaine. A major obstacle to the clinical application of CocE is the thermoinstability of native CocE with a half-life of only ∼11 min at physiological temperature (37 °C). It is highly desirable to develop a thermostable mutant of CocE for therapeutic treatment of cocaine overdose and addiction. To establish a structure-thermostability relationship, we carried out molecular dynamics (MD) simulations at 400 K on wild-type CocE and previously known thermostable mutants, demonstrating that the thermostability of the active form of the enzyme correlates with the fluctuation (characterized as the root-mean square deviation and root-mean square fluctuation of atomic positions) of the catalytic residues (Y44, S117, Y118, H287, and D259) in the simulated enzyme. In light of the structure-thermostability correlation, further computational modelling including MD simulations at 400 K predicted that the active site structure of the L169K mutant should be more thermostable. The prediction has been confirmed by wet experimental tests showing that the active form of the L169K mutant had a half-life of 570 min at 37 °C, which is significantly longer than those of the wild-type and previously known thermostable mutants. The encouraging outcome suggests that the high-temperature MD simulations and the structure-thermostability relationship may be considered as a valuable tool for the computational design of thermostable mutants of an enzyme.

HomoSAR: bridging comparative protein modeling with quantitative structural activity relationship to design new peptides.

PubMed

Borkar, Mahesh R; Pissurlenkar, Raghuvir R S; Coutinho, Evans C

2013-11-15

Peptides play significant roles in the biological world. To optimize activity for a specific therapeutic target, peptide library synthesis is inevitable; which is a time consuming and expensive. Computational approaches provide a promising way to simply elucidate the structural basis in the design of new peptides. Earlier, we proposed a novel methodology termed HomoSAR to gain insight into the structure activity relationships underlying peptides. Based on an integrated approach, HomoSAR uses the principles of homology modeling in conjunction with the quantitative structural activity relationship formalism to predict and design new peptide sequences with the optimum activity. In the present study, we establish that the HomoSAR methodology can be universally applied to all classes of peptides irrespective of sequence length by studying HomoSAR on three peptide datasets viz., angiotensin-converting enzyme inhibitory peptides, CAMEL-s antibiotic peptides, and hAmphiphysin-1 SH3 domain binding peptides, using a set of descriptors related to the hydrophobic, steric, and electronic properties of the 20 natural amino acids. Models generated for all three datasets have statistically significant correlation coefficients (r(2)) and predictive r2 (r(pred)2) and cross validated coefficient ( q(LOO)2). The daintiness of this technique lies in its simplicity and ability to extract all the information contained in the peptides to elucidate the underlying structure activity relationships. The difficulties of correlating both sequence diversity and variation in length of the peptides with their biological activity can be addressed. The study has been able to identify the preferred or detrimental nature of amino acids at specific positions in the peptide sequences. Copyright © 2013 Wiley Periodicals, Inc.

Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

PubMed

Mendenhall, Jeffrey; Meiler, Jens

2016-02-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

Improving Quantitative Structure-Activity Relationship Models using Artificial Neural Networks Trained with Dropout

PubMed Central

Mendenhall, Jeffrey; Meiler, Jens

2016-01-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery (LB-CADD) pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both Enrichment false positive rate (FPR) and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22–46% over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods. PMID:26830599

Abnormalities of thalamic activation and cognition in schizophrenia.

PubMed

Andrews, Jessica; Wang, Lei; Csernansky, John G; Gado, Mokhtar H; Barch, Deanna M

2006-03-01

Functional and structural magnetic resonance imaging (MRI) was used to investigate relationships among structure, functional activation, and cognitive deficits related to the thalamus in individuals with schizophrenia and healthy comparison subjects. Thirty-six schizophrenia subjects and 28 healthy comparison subjects matched by age, gender, race, and parental socioeconomic status underwent structural and functional MRI while performing a series of memory tasks, including an N-back task (working memory), intentional memorization of a series of pictures or words (episodic encoding), and a yes/no recognition task. Functional activation magnitudes in seven regions of interest within the thalamic complex, as defined by anatomical and functional criteria, were computed for each group. Participants with schizophrenia exhibited decreased activation within the whole thalamus, the anterior nuclei, and the medial dorsal nucleus. These nuclei overlap with subregions of the thalamic surface that the authors previously reported to exhibit morphological abnormalities in schizophrenia. However, there were no significant correlations between specific dimensions of thalamic shape variation (i.e., eigenvectors) and the activation patterns within thalamic regions of interest. Better performance on the working memory task among individuals with schizophrenia was significantly associated with increased activation in the anterior nuclei, the centromedian nucleus, the pulvinar, and the ventrolateral nuclei. These results suggest that there are limited relationships between morphological and functional abnormalities of the thalamus in schizophrenia subjects and highlight the importance of investigating relationships between brain structure and function.

Perspective on computational and structural aspects of kinase discovery from IPK2014.

PubMed

Martin, Eric; Knapp, Stefan; Engh, Richard A; Moebitz, Henrik; Varin, Thibault; Roux, Benoit; Meiler, Jens; Berdini, Valerio; Baumann, Alexander; Vieth, Michal

2015-10-01

Recent advances in understanding the activity and selectivity of kinase inhibitors and their relationships to protein structure are presented. Conformational selection in kinases is studied from empirical, data-driven and simulation approaches. Ligand binding and its affinity are, in many cases, determined by the predetermined active and inactive conformation of kinases. Binding affinity and selectivity predictions highlight the current state of the art and advances in computational chemistry as it applies to kinase inhibitor discovery. Kinome wide inhibitor profiling and cell panel profiling lead to a better understanding of selectivity and allow for target validation and patient tailoring hypotheses. This article is part of a Special Issue entitled: Inhibitors of Protein Kinases. Copyright © 2015 Elsevier B.V. All rights reserved.

Antitumor potential of crown ethers: structure-activity relationships, cell cycle disturbances, and cell death studies of a series of ionophores.

PubMed

Marjanović, Marko; Kralj, Marijeta; Supek, Fran; Frkanec, Leo; Piantanida, Ivo; Smuc, Tomislav; Tusek-Bozić, Ljerka

2007-03-08

The present paper demonstrates the antiproliferative ability and structure-activity relationships (SAR) of 14 crown and aza-crown ether analogues on five tumor-cell types. The most active compounds were di-tert-butyldicyclohexano-18-crown-6 (3), which exhibited cytotoxicity in the submicromolar range, and di-tert-butyldibenzo-18-crown-6 (5) (IC50 values of approximately 2 microM). Also, 3 and 5 induced marked influence on the cell cycle phase distribution--strong G1 arrest, followed by the induction of apoptosis. A computational SAR modeling effort offers insight into possible mechanisms of crown ether biological activity, presumably involving penetration into cell membranes, and points out structural features of molecules important for this activity. The results reveal that crown ethers possess marked tumor-cell growth inhibitory activity, the extent of which depends on the characteristics of the hydrophilic macrocylic cavity and the surrounding hydrophobic ring. Our work supports the hypothesis that crown ether compounds inhibit tumor-cell growth by disrupting potassium ion homeostasis, which in turn leads to cell cycle perturbations and apoptosis.

Potential fluid mechanic pathways of platelet activation.

PubMed

Shadden, Shawn C; Hendabadi, Sahar

2013-06-01

Platelet activation is a precursor for blood clotting, which plays leading roles in many vascular complications and causes of death. Platelets can be activated by chemical or mechanical stimuli. Mechanically, platelet activation has been shown to be a function of elevated shear stress and exposure time. These contributions can be combined by considering the cumulative stress or strain on a platelet as it is transported. Here, we develop a framework for computing a hemodynamic-based activation potential that is derived from a Lagrangian integral of strain rate magnitude. We demonstrate that such a measure is generally maximized along, and near to, distinguished material surfaces in the flow. The connections between activation potential and these structures are illustrated through stenotic flow computations. We uncover two distinct structures that may explain observed thrombus formation at the apex and downstream of stenoses. More broadly, these findings suggest fundamental relationships may exist between potential fluid mechanic pathways for mechanical platelet activation and the mechanisms governing their transport.

Potential fluid mechanic pathways of platelet activation

PubMed Central

Shadden, Shawn C.; Hendabadi, Sahar

2012-01-01

Platelet activation is a precursor for blood clotting, which plays leading roles in many vascular complications and causes of death. Platelets can be activated by chemical or mechanical stimuli. Mechanically, platelet activation has been shown to be a function of elevated shear stress and exposure time. These contributions can be combined by considering the cumulative stress or strain on a platelet as it is transported. Here we develop a framework for computing a hemodynamic-based activation potential that is derived from a Lagrangian integral of strain rate magnitude. We demonstrate that such a measure is generally maximized along, and near to, distinguished material surfaces in the flow. The connections between activation potential and these structures are illustrated through stenotic flow computations. We uncover two distinct structures that may explain observed thrombus formation at the apex and downstream of stenoses. More broadly, these findings suggest fundamental relationships may exist between potential fluid mechanic pathways for mechanical platelet activation and the mechanisms governing their transport. PMID:22782543

Structure-Activity Relationship and Molecular Mechanics Reveal the Importance of Ring Entropy in the Biosynthesis and Activity of a Natural Product.

PubMed

Tran, Hai L; Lexa, Katrina W; Julien, Olivier; Young, Travis S; Walsh, Christopher T; Jacobson, Matthew P; Wells, James A

2017-02-22

Macrocycles are appealing drug candidates due to their high affinity, specificity, and favorable pharmacological properties. In this study, we explored the effects of chemical modifications to a natural product macrocycle upon its activity, 3D geometry, and conformational entropy. We chose thiocillin as a model system, a thiopeptide in the ribosomally encoded family of natural products that exhibits potent antimicrobial effects against Gram-positive bacteria. Since thiocillin is derived from a genetically encoded peptide scaffold, site-directed mutagenesis allows for rapid generation of analogues. To understand thiocillin's structure-activity relationship, we generated a site-saturation mutagenesis library covering each position along thiocillin's macrocyclic ring. We report the identification of eight unique compounds more potent than wild-type thiocillin, the best having an 8-fold improvement in potency. Computational modeling of thiocillin's macrocyclic structure revealed a striking requirement for a low-entropy macrocycle for activity. The populated ensembles of the active mutants showed a rigid structure with few adoptable conformations while inactive mutants showed a more flexible macrocycle which is unfavorable for binding. This finding highlights the importance of macrocyclization in combination with rigidifying post-translational modifications to achieve high-potency binding.

Analysis of the relationship between end-to-end distance and activity of single-chain antibody against colorectal carcinoma.

PubMed

Zhang, Jianhua; Liu, Shanhong; Shang, Zhigang; Shi, Li; Yun, Jun

2012-08-22

We investigated the relationship of End-to-end distance between VH and VL with different peptide linkers and the activity of single-chain antibodies by computer-aided simulation. First, we developed (G4S)n (where n = 1-9) as the linker to connect VH and VL, and estimated the 3D structure of single-chain Fv antibody (scFv) by homologous modeling. After molecular models were evaluated and optimized, the coordinate system of every protein was built and unified into one coordinate system, and End-to-end distances calculated using 3D space coordinates. After expression and purification of scFv-n with (G4S)n as n = 1, 3, 5, 7 or 9, the immunoreactivity of purified ND-1 scFv-n was determined by ELISA. A multi-factorial relationship model was employed to analyze the structural factors affecting scFv: rn=ABn-ABO2+CDn-CDO2+BCn-BCst2. The relationship between immunoreactivity and r-values revealed that fusion protein structure approached the desired state when the r-value = 3. The immunoreactivity declined as the r-value increased, but when the r-value exceeded a certain threshold, it stabilized. We used a linear relationship to analyze structural factors affecting scFv immunoreactivity.

Online social activity reflects economic status

NASA Astrophysics Data System (ADS)

Liu, Jin-Hu; Wang, Jun; Shao, Junming; Zhou, Tao

2016-09-01

To characterize economic development and diagnose the economic health condition, several popular indices such as gross domestic product (GDP), industrial structure and income growth are widely applied. However, computing these indices based on traditional economic census is usually costly and resources consuming, and more importantly, following a long time delay. In this paper, we analyzed nearly 200 million users' activities for four consecutive years in the largest social network (Sina Microblog) in China, aiming at exploring latent relationships between the online social activities and local economic status. Results indicate that online social activity has a strong correlation with local economic development and industrial structure, and more interestingly, allows revealing the macro-economic structure instantaneously with nearly no cost. Beyond, this work also provides a new venue to identify risky signal in local economic structure.

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches.

PubMed

Luo, Yao; Wang, Ling

2017-11-16

The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

PubMed Central

Putz, Mihai V.; Duda-Seiman, Corina; Duda-Seiman, Daniel; Putz, Ana-Maria; Alexandrescu, Iulia; Mernea, Maria; Avram, Speranta

2016-01-01

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. PMID:27399692

Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

From bird's eye views to molecular communities: two-layered visualization of structure-activity relationships in large compound data sets

NASA Astrophysics Data System (ADS)

Kayastha, Shilva; Kunimoto, Ryo; Horvath, Dragos; Varnek, Alexandre; Bajorath, Jürgen

2017-11-01

The analysis of structure-activity relationships (SARs) becomes rather challenging when large and heterogeneous compound data sets are studied. In such cases, many different compounds and their activities need to be compared, which quickly goes beyond the capacity of subjective assessments. For a comprehensive large-scale exploration of SARs, computational analysis and visualization methods are required. Herein, we introduce a two-layered SAR visualization scheme specifically designed for increasingly large compound data sets. The approach combines a new compound pair-based variant of generative topographic mapping (GTM), a machine learning approach for nonlinear mapping, with chemical space networks (CSNs). The GTM component provides a global view of the activity landscapes of large compound data sets, in which informative local SAR environments are identified, augmented by a numerical SAR scoring scheme. Prioritized local SAR regions are then projected into CSNs that resolve these regions at the level of individual compounds and their relationships. Analysis of CSNs makes it possible to distinguish between regions having different SAR characteristics and select compound subsets that are rich in SAR information.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

Computer-assisted determination of minimum energy conformations. 7: A pharmacophore model of the active region of the alpha2-adrenoceptor

NASA Astrophysics Data System (ADS)

Ashman, William P.; Mickiewicz, A. P.; Nelson, Todd M.

1992-09-01

Molecular modeling and computational chemistry techniques are used to analyze compounds in developing pharmacophores of biological receptors to use as templates in structure activity relationship studies and to design new chemicals having physiological activity of interest. In this study, the results of x-ray crystal analyses and PM3 semi-empirical molecular orbital conformational analyses are used to determine the three-dimensional representations of selected adrenergic compounds known to be agonists with the alpha2-adrenoceptor in achieving optimized geometries and electrostatic parameters. The alpha2-adrenergic agonists interact with the adrenergic system receptors to produce various increases or decreases in hemodynamic responses (i.e., hypertension, hypotension, and bradycardia) and sedation. A pharmacophore model of the active region of the alpha2-adrenoceptor is described based on the superimposition of common structural, electrostatic, and physicochemical features of the compounds. Using the model to predict compound adrenergic activity and to design alpha2-adrenergic compounds is discussed.

Development of quantitative structure-activity relationships and its application in rational drug design.

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

Over forty years have elapsed since Hansch and Fujita published their pioneering work of quantitative structure-activity relationships (QSAR). Following the introduction of Comparative Molecular Field Analysis (CoMFA) by Cramer in 1998, other three-dimensional QSAR methods have been developed. Currently, combination of classical QSAR and other computational techniques at three-dimensional level is of greatest interest and generally used in the process of modern drug discovery and design. During the last several decades, a number of different mythologies incorporating a range of molecular descriptors and different statistical regression ways have been proposed and successfully applied in developing of new drugs, thus QSAR method has been proven to be indispensable in not only the reliable prediction of specific properties of new compounds, but also the help to elucidate the possible molecular mechanism of the receptor-ligand interactions. Here, we review the recent developments in QSAR and their applications in rational drug design, focusing on the reasonable selection of novel molecular descriptors and the construction of predictive QSAR models by the help of advanced computational techniques.

Scalable total synthesis and comprehensive structure-activity relationship studies of the phytotoxin coronatine.

PubMed

Littleson, Mairi M; Baker, Christopher M; Dalençon, Anne J; Frye, Elizabeth C; Jamieson, Craig; Kennedy, Alan R; Ling, Kenneth B; McLachlan, Matthew M; Montgomery, Mark G; Russell, Claire J; Watson, Allan J B

2018-03-16

Natural phytotoxins are valuable starting points for agrochemical design. Acting as a jasmonate agonist, coronatine represents an attractive herbicidal lead with novel mode of action, and has been an important synthetic target for agrochemical development. However, both restricted access to quantities of coronatine and a lack of a suitably scalable and flexible synthetic approach to its constituent natural product components, coronafacic and coronamic acids, has frustrated development of this target. Here, we report gram-scale production of coronafacic acid that allows a comprehensive structure-activity relationship study of this target. Biological assessment of a >120 member library combined with computational studies have revealed the key determinants of potency, rationalising hypotheses held for decades, and allowing future rational design of new herbicidal leads based on this template.

Relationship between Structural Characteristics of Activated Carbons and Their Concentrating Efficiency with Respect to Nitroorganics.

PubMed

Leboda, R.; Gun'ko, V. M.; Tomaszewski, W.; Trznadel, B. J.

2001-07-15

The relationships between structural properties of activated microporous, micro-mesoporous, mesoporous, and graphitized carbons determined on the basis of nitrogen adsorption at 77.4 K and the efficiency of concentrating (solid-phase extraction (SPE) technique) several nitroorganic compounds from polar solvents were investigated. Microporosity, mesoporosity, fractality, and other characteristics of adsorbents were analyzed to evaluate the dependence of the effectiveness of the SPE technique with respect to nitrate esters, cyclic nitroamines, and nitroaromatics on the origin and texture of carbons. The values of the free energy of solvation and dipole moment of nitroorganic compounds in polar liquids computed with the SM5.42/PM3 method with consideration of geometry relaxation in solution were utilized to elucidate features of their concentration of carbon adsorbents. Copyright 2001 Academic Press.

Aconitum and Delphinium sp. Alkaloids as Antagonist Modulators of Voltage-Gated Na+ Channels. AM1/DFT Electronic Structure Investigations and QSAR Studies

PubMed Central

Turabekova, Malakhat A.; Rasulev, Bakhtiyor F.; Levkovich, Mikhail G.; Abdullaev, Nasrulla D.; Leszczynski, Jerzy

2015-01-01

Early pharmacological studies of Aconitum and Delphinium sp. alkaloids suggested that these neurotoxins act at site 2 of voltage-gated Na+ channel and allosterically modulate its function. Understanding structural requirements for these compounds to exhibit binding activity at voltage-gated Na+ channel has been important in various fields. This paper reports quantum-chemical studies and quantitative structure-activity relationships (QSARs) based on a total of 65 natural alkaloids from two plant species, which includes both blockers and openers of sodium ion channel. A series of 18 antagonist alkaloids (9 blockers and 9 openers) have been studied using AM1 and DFT computational methods in order to reveal their structure-activity (structure-toxicity) relationship at electronic level. An examination of frontier orbitals obtained for ground and protonated forms of the compounds revealed that HOMOs and LUMOs were mainly represented by nitrogen atom and benzyl/benzoylester orbitals with –OH and –OCOCH3 contributions. The results obtained from this research have confirmed the experimental findings suggesting that neurotoxins acting at type 2 receptor site of voltage-dependent sodium channel are activators and blockers with common structural features and differ only in efficacy. The energetic tendency of HOMO-LUMO energy gap can probably distinguish activators and blockers that have been observed. Genetic Algorithm with Multiple Linear Regression Analysis (GA-MLRA) technique was also applied for the generation of two-descriptor QSAR models for the set of 65 blockers. Additionally to the computational studies, the HOMO-LUMO gap descriptor in each obtained QSAR model has confirmed the crucial role of charge transfer in receptor-ligand interactions. A number of other descriptors such as logP, IBEG, nNH2, nHDon, nCO have been selected as complementary ones to LUMO and their role in activity alteration has also been discussed. PMID:18201930

Pharmacological and structure-activity relationship evaluation of 4-aryl-1-diphenylacetyl(thio)semicarbazides.

PubMed

Wujec, Monika; Kędzierska, Ewa; Kuśmierz, Edyta; Plech, Tomasz; Wróbel, Andrzej; Paneth, Agata; Orzelska, Jolanta; Fidecka, Sylwia; Paneth, Piotr

2014-04-16

This article describes the synthesis of six 4-aryl-(thio)semicarbazides (series a and b) linked with diphenylacetyl moiety along with their pharmacological evaluation on the central nervous system in mice and computational studies, including conformational analysis and electrostatic properties. All thiosemicarbazides (series b) were found to exhibit strong antinociceptive activity in the behavioural model. Among them, compound 1-diphenylacetyl-4-(4-methylphenyl)thiosemicarbazide 1b was found to be the most potent analgesic agent, whose activity is connected with the opioid system. For compounds from series a significant anti-serotonergic effect, especially for compound 1-diphenylacetyl-4-(4-methoxyphenyl)semicarbazide 2b was observed. The computational studies strongly support the obtained results.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models

PubMed Central

Zhu, Hao

2017-01-01

Quantitative Structure Activity Relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has been used extensively in drug discovery process. However, the predictive models resulted from QSAR studies have limited use for chemical risk assessment, especially for animal and human toxicity evaluations, due to the low predictivity of new compounds. To develop enhanced toxicity models with independently validated external prediction power, novel modeling protocols were pursued by computational toxicologists based on rapidly increasing toxicity testing data in recent years. This chapter reviews the recent effort in our laboratory to incorporate the biological testing results as descriptors in the toxicity modeling process. This effort extended the concept of QSAR to Quantitative Structure In vitro-In vivo Relationship (QSIIR). The QSIIR study examples provided in this chapter indicate that the QSIIR models that based on the hybrid (biological and chemical) descriptors are indeed superior to the conventional QSAR models that only based on chemical descriptors for several animal toxicity endpoints. We believe that the applications introduced in this review will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment. PMID:23086837

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

Design of an activity landscape view taking compound-based feature probabilities into account.

PubMed

Zhang, Bijun; Vogt, Martin; Bajorath, Jürgen

2014-09-01

Activity landscapes (ALs) of compound data sets are rationalized as graphical representations that integrate similarity and potency relationships between active compounds. ALs enable the visualization of structure-activity relationship (SAR) information and are thus computational tools of interest for medicinal chemistry. For AL generation, similarity and potency relationships are typically evaluated in a pairwise manner and major AL features are assessed at the level of compound pairs. In this study, we add a conditional probability formalism to AL design that makes it possible to quantify the probability of individual compounds to contribute to characteristic AL features. Making this information graphically accessible in a molecular network-based AL representation is shown to further increase AL information content and helps to quickly focus on SAR-informative compound subsets. This feature probability-based AL variant extends the current spectrum of AL representations for medicinal chemistry applications.

Establishing a relationship between maximum torque production of isolated joints to simulate EVA ratchet push-pull maneuver: A case study

NASA Technical Reports Server (NTRS)

Pandya, Abhilash; Maida, James; Hasson, Scott; Greenisen, Michael; Woolford, Barbara

1993-01-01

As manned exploration of space continues, analytical evaluation of human strength characteristics is critical. These extraterrestrial environments will spawn issues of human performance which will impact the designs of tools, work spaces, and space vehicles. Computer modeling is an effective method of correlating human biomechanical and anthropometric data with models of space structures and human work spaces. The aim of this study is to provide biomechanical data from isolated joints to be utilized in a computer modeling system for calculating torque resulting from any upper extremity motions: in this study, the ratchet wrench push-pull operation (a typical extravehicular activity task). Established here are mathematical relationships used to calculate maximum torque production of isolated upper extremity joints. These relationships are a function of joint angle and joint velocity.

Using ToxCast in vitro Assays in the Hierarchical Quantitative Structure-Activity Relationship (QSAR) Modeling for Predicting in vivo Toxicity of Chemicals

EPA Science Inventory

The goal of chemical toxicology research is utilizing short term bioassays and/or robust computational methods to predict in vivo toxicity endpoints for chemicals. The ToxCast program established at the US Environmental Protection Agency (EPA) is addressing this goal by using ca....

Computer-Aided Drug Design in Epigenetics

NASA Astrophysics Data System (ADS)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-03-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

Computer-Aided Drug Design in Epigenetics

PubMed Central

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-01-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. PMID:29594101

Electronic structure contributions to reactivity in xanthine oxidase family enzymes.

PubMed

Stein, Benjamin W; Kirk, Martin L

2015-03-01

We review the xanthine oxidase (XO) family of pyranopterin molybdenum enzymes with a specific emphasis on electronic structure contributions to reactivity. In addition to xanthine and aldehyde oxidoreductases, which catalyze the two-electron oxidation of aromatic heterocycles and aldehyde substrates, this mini-review highlights recent work on the closely related carbon monoxide dehydrogenase (CODH) that catalyzes the oxidation of CO using a unique Mo-Cu heterobimetallic active site. A primary focus of this mini-review relates to how spectroscopy and computational methods have been used to develop an understanding of critical relationships between geometric structure, electronic structure, and catalytic function.

Modeling of the relationship between dipeptide structure and dipeptide stability, permeability, and ACE inhibitory activity.

PubMed

Foltz, Martin; van Buren, Leo; Klaffke, Werner; Duchateau, Guus S M J E

2009-09-01

Selected di- and tripeptides exhibit angiotensin-I converting enzyme (ACE) inhibitory activity in vitro. However, the efficacy in vivo is most likely limited for most peptides due to low bioavailability. The purpose of this study was to identify descriptors of intestinal stability, permeability, and ACE inhibitory activity of dipeptides. A total of 228 dipeptides were synthesized; intestinal stability was obtained by in vitro digestion, intestinal permeability using Caco-2 cells and ACE inhibitory activity by an in vitro assay. Databases were constructed to study the relationship between structure and activity, permeability, and stability. Quantitative structure-activity relationship (QSAR) modeling was performed based on computed models using partial least squares regression based on 400 molecular descriptors. QSAR modeling of dipeptide stability revealed high correlation coefficients (R > 0.65) for models based on Z and X scales. However, amino acid (AA) clustering showed the best results in describing stability of dipeptides. The N-terminal AA residues Asp, Gly, and Pro as well as the C-terminal residues Pro, Ser, Thr, and Asp stabilize dipeptides toward luminal enzymatic peptide hydrolysis. QSAR modeling did not reveal significant correlation models for intestinal permeability. 2D-fingerprint models were identified describing ACE inhibitory activity of dipeptides. The intestinal stability of 12 peptides was predicted. Peptides were synthesized and stability was confirmed in simulated digestion experiments. Based on the results, specific dipeptides can be designed to meet both stability and activity criteria. However, postabsorptive ACE inhibitory activities of dipeptides in vivo are most likely limited due to the very low intestinal permeability of dipeptides.

Deep neural nets as a method for quantitative structure-activity relationships.

PubMed

Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

2015-02-23

Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

Derivatives of Ergot-alkaloids: Molecular structure, physical properties, and structure-activity relationships

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka B.; Spiteller, Michael

2012-09-01

A comprehensive screening of fifteen functionalized Ergot-alkaloids, containing bulk aliphatic cyclic substituents at D-ring of the ergoline molecular skeleton was performed, studying their structure-active relationships and model interactions with α2A-adreno-, serotonin (5HT2A) and dopamine D3 (D3A) receptors. The accounted high affinity to the receptors binding loops and unusual bonding situations, joined with the molecular flexibility of the substituents and the presence of proton accepting/donating functional groups in the studied alkaloids, may contribute to further understanding the mechanisms of biological activity in vivo and in predicting their therapeutic potential in central nervous system (CNS), including those related the Schizophrenia. Since the presented correlation between the molecular structure and properties, was based on the comprehensively theoretical computational and experimental physical study on the successfully isolated derivatives, through using routine synthetic pathways in a relatively high yields, marked these derivatives as 'treasure' for further experimental and theoretical studied in areas such as: (a) pharmacological and clinical testing; (b) molecular-drugs design of novel psychoactive substances; (c) development of the analytical protocols for determination of Ergot-alkaloids through a functionalization of the ergoline-skeleton, and more.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

PubMed

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W

2012-12-01

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.

Linking structure and activity in nonlinear spiking networks

PubMed Central

Josić, Krešimir; Shea-Brown, Eric

2017-01-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks’ spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities—including those of different cell types—combine with connectivity to shape population activity and function. PMID:28644840

Structure-activity relationships of diphenyl-ether as protoporphyrinogen oxidase inhibitors: insights from computational simulations

NASA Astrophysics Data System (ADS)

Hao, Ge-Fei; Tan, Ying; Yu, Ning-Xi; Yang, Guang-Fu

2011-03-01

Protoporphyrinogen oxidase (PPO, EC 1.3.3.4), which has been identified as a significant target for a great family of herbicides with diverse chemical structures, is the last common enzyme responsible for the seventh step in the biosynthetic pathway to heme and chlorophyll. Among the existing PPO inhibitors, diphenyl-ether is the first commercial family of PPO inhibitors and used as agriculture herbicides for decades. Most importantly, diphenyl-ether inhibitors have been found recently to possess the potential in Photodynamic therapy (PDT) to treat cancer. Herein, molecular dynamics simulations, approximate free energy calculations and hydrogen bond energy calculations were integrated together to uncover the structure-activity relationships of this type of PPO inhibitors. The calculated binding free energies are correlated very well with the values derived from the experimental k i data. According to the established computational models and the results of approximate free energy calculation, the substitution effects at different position were rationalized from the view of binding free energy. Some outlier ( e.g. LS) in traditional QSAR study can also be explained reasonably. In addition, the hydrogen bond energy calculation and interaction analysis results indicated that the carbonyl oxygen on position-9 and the NO2 group at position-8 are both vital for the electrostatic interaction with Arg98, which made a great contribution to the binding free energy. These insights from computational simulations are not only helpful for understanding the molecular mechanism of PPO-inhibitor interactions, but also beneficial to the future rational design of novel promising PPO inhibitors.

Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity.

PubMed

Zhou, Peng; Wang, Congcong; Tian, Feifei; Ren, Yanrong; Yang, Chao; Huang, Jian

2013-01-01

Quantitative structure-activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482-491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.

Computer graphics in architecture and engineering

NASA Technical Reports Server (NTRS)

Greenberg, D. P.

1975-01-01

The present status of the application of computer graphics to the building profession or architecture and its relationship to other scientific and technical areas were discussed. It was explained that, due to the fragmented nature of architecture and building activities (in contrast to the aerospace industry), a comprehensive, economic utilization of computer graphics in this area is not practical and its true potential cannot now be realized due to the present inability of architects and structural, mechanical, and site engineers to rely on a common data base. Future emphasis will therefore have to be placed on a vertical integration of the construction process and effective use of a three-dimensional data base, rather than on waiting for any technological breakthrough in interactive computing.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Quantum chemical parameters in QSAR: what do I use when?

USGS Publications Warehouse

Hickey, James P.; Ostrander, Gary K.

1996-01-01

This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

Electronic Structure Contributions to Reactivity in Xanthine Oxidase Family Enzymes

PubMed Central

Stein, Benjamin W.; Kirk, Martin L.

2016-01-01

We review the xanthine oxidase (XO) family of pyranopterin molybdenum enzymes with a specific emphasis on electronic structure contributions to reactivity. In addition to xanthine and aldehyde oxidoreductases, which catalyze the 2-electron oxidation of aromatic heterocycles and aldehyde substrates, this mini-review highlights recent work on the closely related carbon monoxide dehydrogenase (CODH) that catalyzes the oxidation of CO using a unique Mo-Cu heterobimetallic active site. A primary focus of this mini-review relates to how spectroscopy and computational methods have been used to develop an understanding of critical relationships between geometric structure, electronic structure, and catalytic function. PMID:25425163

Computational Design of a Thermostable Mutant of Cocaine Esterase via Molecular Dynamics Simulations

PubMed Central

Huang, Xiaoqin; Gao, Daquan; Zhan, Chang-Guo

2015-01-01

Cocaine esterase (CocE) has been known as the most efficient native enzyme for metabolizing the naturally occurring cocaine. A major obstacle to the clinical application of CocE is the thermoinstability of native CocE with a half-life of only ~11 min at physiological temperature (37°C). It is highly desirable to develop a thermostable mutant of CocE for therapeutic treatment of cocaine overdose and addiction. To establish a structure-thermostability relationship, we carried out molecular dynamics (MD) simulations at 400 K on wild-type CocE and previously known thermostable mutants, demonstrating that the thermostability of the active form of the enzyme correlates with the fluctuation (characterized as the RMSD and RMSF of atomic positions) of the catalytic residues (Y44, S117, Y118, H287, and D259) in the simulated enzyme. In light of the structure-thermostability correlation, further computational modeling including MD simulations at 400 K predicted that the active site structure of the L169K mutant should be more thermostable. The prediction has been confirmed by wet experimental tests showing that the active form of the L169K mutant had a half-life of 570 min at 37°C, which is significantly longer than those of the wild-type and previously known thermostable mutants. The encouraging outcome suggests that the high-temperature MD simulations and the structure-thermostability may be considered as a valuable tool for computational design of thermostable mutants of an enzyme. PMID:21373712

The Use of Multiscale Molecular Simulations in Understanding a Relationship between the Structure and Function of Biological Systems of the Brain: The Application to Monoamine Oxidase Enzymes

PubMed Central

Vianello, Robert; Domene, Carmen; Mavri, Janez

2016-01-01

HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic activities and their inhibition. As an illustrative example, the later will focus on the monoamine oxidase family of enzymes, which catalyze the degradation of amine neurotransmitters in various parts of the brain, the imbalance of which is associated with the development and progression of a range of neurodegenerative disorders. Inhibitors that act mainly on MAO A are used in the treatment of depression, due to their ability to raise serotonin concentrations, while MAO B inhibitors decrease dopamine degradation and improve motor control in patients with Parkinson disease. Our results give strong support that both MAO isoforms, A and B, operate through the hydride transfer mechanism. Relevance of MAO catalyzed reactions and MAO inhibition in the context of neurodegeneration will be discussed. PMID:27471444

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

PubMed

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens.

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

PubMed Central

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

EPA Science Inventory

Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

Biocatalysis and biomimetics

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

Burrington, J.D.; Clark, D.S.

1989-01-01

This book presents recent advances in catalytic science and biotechnology. The chapters illustrate how many of the key challenges in biotechnology can be addressed by bringing together traditionally separate disciplines within chemistry and biology. The authors focus on emerging enabling technologies at the interfaces of catalysis and biology that will provide new opportunities for the chemicals industries. Key aspects to be presented within this major theme of catalysis and biotechnology are biomimetics and hybrid catalysts, biocatalytic applications of computers and expert systems, enzyme solid-state structure and immobilization, enzyme structure-activity relationships, and the use of enzymes under novel conditions.

CONSIDERATION OF REACTION INTERMEDIATES IN STRUCTURE-ACTIVITY RELATIONSHIPS: A KEY TO UNDERSTANDING AND PREDICTION

EPA Science Inventory

Consideration of Reaction Intermediates in Structure- Activity Relationships: A Key to Understanding and Prediction

A structure-activity relationship (SAR) represents an empirical means for generalizing chemical information relative to biological activity, and is frequent...

Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music.

PubMed

Agres, Kat; Herremans, Dorien; Bigo, Louis; Conklin, Darrell

2016-01-01

An empirical investigation of how local harmonic structures (e.g., chord progressions) contribute to the experience and enjoyment of uplifting trance (UT) music is presented. The connection between rhythmic and percussive elements and resulting trance-like states has been highlighted by musicologists, but no research, to our knowledge, has explored whether repeated harmonic elements influence affective responses in listeners of trance music. Two alternative hypotheses are discussed, the first highlighting the direct relationship between repetition/complexity and enjoyment, and the second based on the theoretical inverted-U relationship described by the Wundt curve. We investigate the connection between harmonic structure and subjective enjoyment through interdisciplinary behavioral and computational methods: First we discuss an experiment in which listeners provided enjoyment ratings for computer-generated UT anthems with varying levels of harmonic repetition and complexity. The anthems were generated using a statistical model trained on a corpus of 100 uplifting trance anthems created for this purpose, and harmonic structure was constrained by imposing particular repetition structures (semiotic patterns defining the order of chords in the sequence) on a professional UT music production template. Second, the relationship between harmonic structure and enjoyment is further explored using two computational approaches, one based on average Information Content, and another that measures average tonal tension between chords. The results of the listening experiment indicate that harmonic repetition does in fact contribute to the enjoyment of uplifting trance music. More compelling evidence was found for the second hypothesis discussed above, however some maximally repetitive structures were also preferred. Both computational models provide evidence for a Wundt-type relationship between complexity and enjoyment. By systematically manipulating the structure of chord progressions, we have discovered specific harmonic contexts in which repetitive or complex structure contribute to the enjoyment of uplifting trance music.

Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music

PubMed Central

Agres, Kat; Herremans, Dorien; Bigo, Louis; Conklin, Darrell

2017-01-01

An empirical investigation of how local harmonic structures (e.g., chord progressions) contribute to the experience and enjoyment of uplifting trance (UT) music is presented. The connection between rhythmic and percussive elements and resulting trance-like states has been highlighted by musicologists, but no research, to our knowledge, has explored whether repeated harmonic elements influence affective responses in listeners of trance music. Two alternative hypotheses are discussed, the first highlighting the direct relationship between repetition/complexity and enjoyment, and the second based on the theoretical inverted-U relationship described by the Wundt curve. We investigate the connection between harmonic structure and subjective enjoyment through interdisciplinary behavioral and computational methods: First we discuss an experiment in which listeners provided enjoyment ratings for computer-generated UT anthems with varying levels of harmonic repetition and complexity. The anthems were generated using a statistical model trained on a corpus of 100 uplifting trance anthems created for this purpose, and harmonic structure was constrained by imposing particular repetition structures (semiotic patterns defining the order of chords in the sequence) on a professional UT music production template. Second, the relationship between harmonic structure and enjoyment is further explored using two computational approaches, one based on average Information Content, and another that measures average tonal tension between chords. The results of the listening experiment indicate that harmonic repetition does in fact contribute to the enjoyment of uplifting trance music. More compelling evidence was found for the second hypothesis discussed above, however some maximally repetitive structures were also preferred. Both computational models provide evidence for a Wundt-type relationship between complexity and enjoyment. By systematically manipulating the structure of chord progressions, we have discovered specific harmonic contexts in which repetitive or complex structure contribute to the enjoyment of uplifting trance music. PMID:28119641

Predicting Catalytic Proton Donors and Nucleophiles in Enzymes: How Adding Dynamics Helps Elucidate the Structure-Function Relationships.

PubMed

Huang, Yandong; Yue, Zhi; Tsai, Cheng-Chieh; Henderson, Jack A; Shen, Jana

2018-03-15

Despite the relevance of understanding structure-function relationships, robust prediction of proton donors and nucleophiles in enzyme active sites remains challenging. Here we tested three types of state-of-the-art computational methods to calculate the p K a 's of the buried and hydrogen bonded catalytic dyads in five enzymes. We asked the question what determines the p K a order, i.e., what makes a residue proton donor vs a nucleophile. The continuous constant pH molecular dynamics simulations captured the experimental p K a orders and revealed that the negative nucleophile is stabilized by increased hydrogen bonding and solvent exposure as compared to the proton donor. Surprisingly, this simple trend is not apparent from crystal structures and the static structure-based calculations. While the generality of the findings awaits further testing via a larger set of data, they underscore the role of dynamics in bridging enzyme structures and functions.

Computational modeling of neural plasticity for self-organization of neural networks.

PubMed

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

What are the ideal properties for functional food peptides with antihypertensive effect? A computational peptidology approach.

PubMed

Zhou, Peng; Yang, Chao; Ren, Yanrong; Wang, Congcong; Tian, Feifei

2013-12-01

Peptides with antihypertensive potency have long been attractive to the medical and food communities. However, serving as food additives, rather than therapeutic agents, peptides should have a good taste. In the present study, we explore the intrinsic relationship between the angiotensin I-converting enzyme (ACE) inhibition and bitterness of short peptides in the framework of computational peptidology, attempting to find out the appropriate properties for functional food peptides with satisfactory bioactivities. As might be expected, quantitative structure-activity relationship modeling reveals a significant positive correlation between the ACE inhibition and bitterness of dipeptides, but this correlation is quite modest for tripeptides and, particularly, tetrapeptides. Moreover, quantum mechanics/molecular mechanics analysis of the structural basis and energetic profile involved in ACE-peptide complexes unravels that peptides of up to 4 amino acids long are sufficient to have efficient binding to ACE, and more additional residues do not bring with substantial enhance in their ACE-binding affinity and, thus, antihypertensive capability. All of above, it is coming together to suggest that the tripeptides and tetrapeptides could be considered as ideal candidates for seeking potential functional food additives with both high antihypertensive activity and low bitterness. Copyright © 2013 Elsevier Ltd. All rights reserved.

Substrate tunnels in enzymes: structure-function relationships and computational methodology.

PubMed

Kingsley, Laura J; Lill, Markus A

2015-04-01

In enzymes, the active site is the location where incoming substrates are chemically converted to products. In some enzymes, this site is deeply buried within the core of the protein, and, in order to access the active site, substrates must pass through the body of the protein via a tunnel. In many systems, these tunnels act as filters and have been found to influence both substrate specificity and catalytic mechanism. Identifying and understanding how these tunnels exert such control has been of growing interest over the past several years because of implications in fields such as protein engineering and drug design. This growing interest has spurred the development of several computational methods to identify and analyze tunnels and how ligands migrate through these tunnels. The goal of this review is to outline how tunnels influence substrate specificity and catalytic efficiency in enzymes with buried active sites and to provide a brief summary of the computational tools used to identify and evaluate these tunnels. © 2015 Wiley Periodicals, Inc.

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.

CSM research: Methods and application studies

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.

1989-01-01

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Identifying relationships between unrelated pharmaceutical target proteins on the basis of shared active compounds.

PubMed

Miljković, Filip; Kunimoto, Ryo; Bajorath, Jürgen

2017-08-01

Computational exploration of small-molecule-based relationships between target proteins from different families. Target annotations of drugs and other bioactive compounds were systematically analyzed on the basis of high-confidence activity data. A total of 286 novel chemical links were established between distantly related or unrelated target proteins. These relationships involved a total of 1859 bioactive compounds including 147 drugs and 141 targets. Computational analysis of large amounts of compounds and activity data has revealed unexpected relationships between diverse target proteins on the basis of compounds they share. These relationships are relevant for drug discovery efforts. Target pairs that we have identified and associated compound information are made freely available.

Structure-activity relationships and prediction of the phototoxicity and phototoxic potential of new drugs.

PubMed

Barratt, Martin D

2004-11-01

Relationships between the structure and properties of chemicals can be programmed into knowledge-based systems such as DEREK for Windows (DEREK is an acronym for "Deductive Estimation of Risk from Existing Knowledge"). The DEREK for Windows computer system contains a subset of over 60 rules describing chemical substructures (toxophores) responsible for skin sensitisation. As part of the European Phototox Project, the rule base was supplemented by a number of rules for the prospective identification of photoallergens, either by extension of the scope of existing rules or by the generation of new rules where a sound mechanistic rationale for the biological activity could be established. The scope of the rules for photoallergenicity was then further refined by assessment against a list of chemicals identified as photosensitisers by the Centro de Farmacovigilancia de la Comunidad Valenciana, Valencia, Spain. This paper contains an analysis of the mechanistic bases of activity for eight important groups of photoallergens and phototoxins, together with rules for the prospective identification of the photobiological activity of new or untested chemicals belonging to those classes. The mechanism of action of one additional chemical, nitrofurantoin, is well established; however, it was deemed inappropriate to write a rule on the basis of a single chemical structure.

A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

PubMed

Sahoo, Sagarika; Adhikari, Chandana; Kuanar, Minati; Mishra, Bijay K

2016-01-01

Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD). This review is a survey on the generation of the molecular descriptors and its probable applications in QSP/AR. Literatures have been collected from a wide class of research journals, citable web reports, seminar proceedings and books. The MDs were classified according to their generation. The applications of the MDs on the QSP/AR have also been reported in this review. The MDs can be classified into experimental and theoretical types, having a sub classification of the later into structural and quantum chemical descriptors. The structural parameters are derived from molecular graphs or topology of the molecules. Even the pixel of the molecular image can be used as molecular descriptor. In QSPR studies the physicochemical properties include boiling point, heat capacity, density, refractive index, molar volume, surface tension, heat of formation, octanol-water partition coefficient, solubility, chromatographic retention indices etc. Among biological activities toxicity, antimalarial activity, sensory irritant, potencies of local anesthetic, tadpole narcosis, antifungal activity, enzyme inhibiting activity are some important parameters in the QSAR studies. The classification of the MDs is mostly generic in nature. The application of the MDs in QSP/AR also has a generic link. Experimental MDs are more suitable in correlation analysis than the theoretical ones but are more expensive for generation. In advent of sophisticated computational tools and experimental design proliferation of MDs is inevitable, but for a highly optimized MD, studies on generation of MD is an unending process.

4-Aminoquinolines Active against Chloroquine-Resistant Plasmodium falciparum: Basis of Antiparasite Activity and Quantitative Structure-Activity Relationship Analyses▿

PubMed Central

Hocart, Simon J.; Liu, Huayin; Deng, Haiyan; De, Dibyendu; Krogstad, Frances M.; Krogstad, Donald J.

2011-01-01

Chloroquine (CQ) is a safe and economical 4-aminoquinoline (AQ) antimalarial. However, its value has been severely compromised by the increasing prevalence of CQ resistance. This study examined 108 AQs, including 68 newly synthesized compounds. Of these 108 AQs, 32 (30%) were active only against CQ-susceptible Plasmodium falciparum strains and 59 (55%) were active against both CQ-susceptible and CQ-resistant P. falciparum strains (50% inhibitory concentrations [IC50s], ≤25 nM). All AQs active against both CQ-susceptible and CQ-resistant P. falciparum strains shared four structural features: (i) an AQ ring without alkyl substitution, (ii) a halogen at position 7 (Cl, Br, or I but not F), (iii) a protonatable nitrogen at position 1, and (iv) a second protonatable nitrogen at the end of the side chain distal from the point of attachment to the AQ ring via the nitrogen at position 4. For activity against CQ-resistant parasites, side chain lengths of ≤3 or ≥10 carbons were necessary but not sufficient; they were identified as essential factors by visual comparison of 2-dimensional (2-D) structures in relation to the antiparasite activities of the AQs and were confirmed by computer-based 3-D comparisons and differential contour plots of activity against P. falciparum. The advantage of the method reported here (refinement of quantitative structure-activity relationship [QSAR] descriptors by random assignment of compounds to multiple training and test sets) is that it retains QSAR descriptors according to their abilities to predict the activities of unknown test compounds rather than according to how well they fit the activities of the compounds in the training sets. PMID:21383099

The Influence of Joint Loading on Bone Marrow Lesions in the Knee: A Systematic Review With Meta-analysis.

PubMed

Beckwée, David; Vaes, Peter; Shahabpour, Maryam; Muyldermans, Ronald; Rommers, Nikki; Bautmans, Ivan

2015-12-01

Bone marrow lesions (BMLs) are considered as predictors of pain, disability, and structural progression of knee osteoarthritis. The relationship between knee loading and BMLs is not yet completely understood. To summarize the available evidence regarding the relationship between joint loading and the prevalence and progression of BMLs in the tibiofemoral joint. Meta-analysis. Three databases (PubMed, Web of Science, and The Cochrane Library) were systematically screened for studies encompassing BMLs and changes in knee loading. A methodological quality assessment was conducted, and a meta-analysis computing overall odds ratios (ORs) was performed where possible. A total of 29 studies involving 7641 participants were included. Mechanical loading was categorized as body weight and composition, compartmental load, structural lesion, and physical activity. High compartmental loads and structural lesions increased the risk for BMLs (overall ORs ranging from 1.56 [95% CI, 1.13-2.15] to 8.2 [95% CI, 4.4-15.1]; P = .006). Body weight increased the risk for BMLs to a lesser extent (overall OR, 1.03; 95% CI, 1.01-1.05; P = .007). Contradictory results for the effect of physical activity on BMLs were found. Augmented compartmental loads and structural lesions increased the risk of the presence or progression of BMLs. Body weight increased the risk for BMLs to a lesser extent. Contradictory results for the effect of physical activity on BMLs may be explained by a dose-response relationship, knee alignment, and structural lesions. It has been shown that unloading the knee temporarily may induce beneficial effects on osteoarthritis-related structural changes. Therefore, an early recognition of BMLs in the aging athlete's knee may provide information to counter the onset and aggravation of symptomatic knee osteoarthritis by reducing the knee load. © 2015 The Author(s).

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.

Innovative computer-aided methods for the discovery of new kinase ligands.

PubMed

Abuhammad, Areej; Taha, Mutasem

2016-04-01

Recent evidence points to significant roles played by protein kinases in cell signaling and cellular proliferation. Faulty protein kinases are involved in cancer, diabetes and chronic inflammation. Efforts are continuously carried out to discover new inhibitors for selected protein kinases. In this review, we discuss two new computer-aided methodologies we developed to mine virtual databases for new bioactive compounds. One method is ligand-based exploration of the pharmacophoric space of inhibitors of any particular biotarget followed by quantitative structure-activity relationship-based selection of the best pharmacophore(s). The second approach is structure-based assuming that potent ligands come into contact with binding site spots distinct from those contacted by weakly potent ligands. Both approaches yield pharmacophores useful as 3D search queries for the discovery of new bioactive (kinase) inhibitors.

Permutation methods for the structured exploratory data analysis (SEDA) of familial trait values.

PubMed

Karlin, S; Williams, P T

1984-07-01

A collection of functions that contrast familial trait values between and across generations is proposed for studying transmission effects and other collateral influences in nuclear families. Two classes of structured exploratory data analysis (SEDA) statistics are derived from ratios of these functions. SEDA-functionals are the empirical cumulative distributions of the ratio of the two contrasts computed within each family. SEDA-indices are formed by first averaging the numerator and denominator contrasts separately over the population and then forming their ratio. The significance of SEDA results are determined by a spectrum of permutation techniques that selectively shuffle the trait values across families. The process systematically alters certain family structure relationships while keeping other familial relationships intact. The methodology is applied to five data examples of plasma total cholesterol concentrations, reported height values, dermatoglyphic pattern intensity index scores, measurements of dopamine-beta-hydroxylase activity, and psychometric cognitive test results.

Computationally mapping sequence space to understand evolutionary protein engineering.

PubMed

Armstrong, Kathryn A; Tidor, Bruce

2008-01-01

Evolutionary protein engineering has been dramatically successful, producing a wide variety of new proteins with altered stability, binding affinity, and enzymatic activity. However, the success of such procedures is often unreliable, and the impact of the choice of protein, engineering goal, and evolutionary procedure is not well understood. We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols. We then tested the ability of different evolutionary search strategies to explore these sequence spaces. The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication. The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search. Moreover, genetic recombination procedures were examined, and tradeoffs relating sequence diversity and search efficiency were identified. This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.

Statistical molecular design of balanced compound libraries for QSAR modeling.

PubMed

Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K

2010-01-01

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

Conflicts of interest improve collective computation of adaptive social structures

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2018-01-01

In many biological systems, the functional behavior of a group is collectively computed by the system’s individual components. An example is the brain’s ability to make decisions via the activity of billions of neurons. A long-standing puzzle is how the components’ decisions combine to produce beneficial group-level outputs, despite conflicts of interest and imperfect information. We derive a theoretical model of collective computation from mechanistic first principles, using results from previous work on the computation of power structure in a primate model system. Collective computation has two phases: an information accumulation phase, in which (in this study) pairs of individuals gather information about their fighting abilities and make decisions about their dominance relationships, and an information aggregation phase, in which these decisions are combined to produce a collective computation. To model information accumulation, we extend a stochastic decision-making model—the leaky integrator model used to study neural decision-making—to a multiagent game-theoretic framework. We then test alternative algorithms for aggregating information—in this study, decisions about dominance resulting from the stochastic model—and measure the mutual information between the resultant power structure and the “true” fighting abilities. We find that conflicts of interest can improve accuracy to the benefit of all agents. We also find that the computation can be tuned to produce different power structures by changing the cost of waiting for a decision. The successful application of a similar stochastic decision-making model in neural and social contexts suggests general principles of collective computation across substrates and scales. PMID:29376116

Characterizing structure connectivity correlation with the default mode network in Alzheimer's patients and normal controls

NASA Astrophysics Data System (ADS)

Guo, Jia; Xu, Peng; Song, Chao; Yao, Li; Zhao, Xiaojie

2012-03-01

Magnetic resonance diffusion tensor imaging (DTI) is a kind of effective measure to do non-invasive investigation on brain fiber structure at present. Studies of fiber tracking based on DTI showed that there was structural connection of white matter fiber among the nodes of resting-state functional network, denoting that the connection of white matter was the basis of gray matter regions in functional network. Nevertheless, relationship between these structure connectivity regions and functional network has not been clearly indicated. Moreover, research of fMRI found that activation of default mode network (DMN) in Alzheimer's disease (AD) was significantly descended, especially in hippocampus and posterior cingulated cortex (PCC). The relationship between this change of DMN activity and structural connection among functional networks needs further research. In this study, fast marching tractography (FMT) algorithm was adopted to quantitative calculate fiber connectivity value between regions, and hippocampus and PCC which were two important regions in DMN related with AD were selected to compute white matter connection region between them in elderly normal control (NC) and AD patient. The fiber connectivity value was extracted to do the correlation analysis with activity intensity of DMN. Results showed that, between PCC and hippocampus of NC, there exited region with significant high connectivity value of white matter fiber whose performance has relatively strong correlation with the activity of DMN, while there was no significant white matter connection region between them for AD patient which might be related with reduced network activation in these two regions of AD.

Structural Reproduction of Social Networks in Computer-Mediated Communication Forums

ERIC Educational Resources Information Center

Stefanone, M. A.; Gay, G.

2008-01-01

This study explores the relationship between the structure of an existing social network and the structure of an emergent discussion-board network in an undergraduate university class. Thirty-one students were issued with laptop computers that remained in their possession for the duration of the semester. While using these machines, participants'…

Proteins with Novel Structure, Function and Dynamics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

Advances in methods to characterize ligand-induced ionic lock and rotamer toggle molecular switch in G protein-coupled receptors.

PubMed

Xie, Xiang-Qun; Chowdhury, Ananda

2013-01-01

Structural biology of GPCRs has made significant progress upon recently developed technologies for GPCRs expression/purification and elucidation of GPCRs crystal structures. The crystal structures provide a snapshot of the receptor structural disposition of GPCRs itself or with cocrystallized ligands, and the results are congruent with biophysical and computer modeling studies reported about GPCRs conformational and dynamics flexibility, regulated activation, and the various stabilizing interactions, such as "molecular switches." The molecular switches generally constitute the most conserved domains within a particular GPCR superfamily. Often agonist-induced receptor activation proceeds by the disruption of majority of these interactions, while antagonist and inverse agonist act as blockers and structural stabilizers, respectively. Several elegant studies, particularly for the β2AR, have demonstrated the relationship between ligand structure, receptor conformational changes, and corresponding pharmacological outcomes. Thus, it is of great importance to understand GPCRs activation related to cell signaling pathways. Herein, we summarize the steps to produce functional GPCRs, generate suitably fluorescent labeled GPCRs and the procedure to use that to understand if ligand-induced activation can proceed by activation of the GPCRs via ionic lock switch and/or rotamer toggle switch mechanisms. Such understanding of ligand structure and mechanism of receptor activation will provide great insight toward uncovering newer pathways of GPCR activation and aid in structure-based drug design. Copyright © 2013 Elsevier Inc. All rights reserved.

[Psychogenetic neurological disorders in draft age personnel].

PubMed

Akhmetianov, L A; Ovchinnikov, A V

2012-07-01

The tendency of psychogenetic neurological disorders increases with predominance in young persons being students of high schools, students of military, technical and other lyceum was shown. The origin of diseases are psychotraumas (family, work), stress. Also genetic and hereditary factors take place that are indicative for individual rehabilitation organization. The basics of psychosomatic diseases pathogenesis are the disintegration mechanisms in brain structure activity,the disorders of integrative apparatus which provides the relationship between somatic, emotional and vegetative functions. The confirmation of brain work disintegration is achieved by modern computer diagnostic systems. As psychogenic diseases increase the need in methods of computer electroencephalography, evoked potentials, and rheoencephalography application is more actual.

Computational modeling approaches to quantitative structure-binding kinetics relationships in drug discovery.

PubMed

De Benedetti, Pier G; Fanelli, Francesca

2018-03-21

Simple comparative correlation analyses and quantitative structure-kinetics relationship (QSKR) models highlight the interplay of kinetic rates and binding affinity as an essential feature in drug design and discovery. The choice of the molecular series, and their structural variations, used in QSKR modeling is fundamental to understanding the mechanistic implications of ligand and/or drug-target binding and/or unbinding processes. Here, we discuss the implications of linear correlations between kinetic rates and binding affinity constants and the relevance of the computational approaches to QSKR modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.

Application of quantitative structure activity relationship (QSAR) models to predict ozone toxicity in the lung.

PubMed

Kafoury, Ramzi M; Huang, Ming-Ju

2005-08-01

The sequence of events leading to ozone-induced airway inflammation is not well known. To elucidate the molecular and cellular events underlying ozone toxicity in the lung, we hypothesized that lipid ozonation products (LOPs) generated by the reaction of ozone with unsaturated fatty acids in the epithelial lining fluid and cell membranes play a key role in mediating ozone-induced airway inflammation. To test our hypothesis, we ozonized 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and generated LOPs. Confluent human bronchial epithelial cells were exposed to the derivatives of ozonized POPC-9-oxononanoyl, 9-hydroxy-9-hydroperoxynonanoyl, and 8-(5-octyl-1,2,4-trioxolan-3-yl-)octanoyl-at a concentration of 10 muM, and the activity of phospholipases A2 (PLA2), C (PLC), and D (PLD) was measured (1, 0.5, and 1 h, respectively). Quantitative structure-activity relationship (QSAR) models were utilized to predict the biological activity of LOPs in airway epithelial cells. The QSAR results showed a strong correlation between experimental and computed activity (r = 0.97, 0.98, 0.99, for PLA2, PLC, and PLD, respectively). The results indicate that QSAR models can be utilized to predict the biological activity of the various ozone-derived LOP species in the lung. Copyright 2005 Wiley Periodicals, Inc.

Elucidation of Peptide-Directed Palladium Surface Structure for Biologically Tunable Nanocatalysts

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

Bedford, Nicholas M.; Ramezani-Dakhel, Hadi; Slocik, Joseph M.

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, whichmore » was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then eluddated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences« less

Elucidation of peptide-directed palladium surface structure for biologically tunable nanocatalysts.

PubMed

Bedford, Nicholas M; Ramezani-Dakhel, Hadi; Slocik, Joseph M; Briggs, Beverly D; Ren, Yang; Frenkel, Anatoly I; Petkov, Valeri; Heinz, Hendrik; Naik, Rajesh R; Knecht, Marc R

2015-05-26

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, which was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then elucidated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences.

Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

PubMed

Chabiniok, Radomir; Wang, Vicky Y; Hadjicharalambous, Myrianthi; Asner, Liya; Lee, Jack; Sermesant, Maxime; Kuhl, Ellen; Young, Alistair A; Moireau, Philippe; Nash, Martyn P; Chapelle, Dominique; Nordsletten, David A

2016-04-06

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

Music and Computing.

ERIC Educational Resources Information Center

Boody, Charles G., Ed.

1986-01-01

Six articles on music and computing address development of computer-based music technology, computer assisted instruction (CAI) in ear training and music fundamentals, a machine-independent data structure for musical pitch relationship representation, touch tablet input device in a melodic dictation CAI game, and systematic evaluation strategies…

THE USE OF STRUCTURE-ACTIVITY RELATIONSHIPS IN INTEGRATING THE CHEMISTRY AND TOXICOLOGY OF ENDOCRINE DISRUPTING CHEMICALS

EPA Science Inventory

Structure activity relationships (SARs) are based on the principle that structurally similar chemicals should have similar biological activity. SARs relate specifically-defined toxicological activity of chemicals to their molecular structure and physico-chemical properties. To de...

An information driven strategy to support multidisciplinary design

NASA Technical Reports Server (NTRS)

Rangan, Ravi M.; Fulton, Robert E.

1990-01-01

The design of complex engineering systems such as aircraft, automobiles, and computers is primarily a cooperative multidisciplinary design process involving interactions between several design agents. The common thread underlying this multidisciplinary design activity is the information exchange between the various groups and disciplines. The integrating component in such environments is the common data and the dependencies that exist between such data. This may be contrasted to classical multidisciplinary analyses problems where there is coupling between distinct design parameters. For example, they may be expressed as mathematically coupled relationships between aerodynamic and structural interactions in aircraft structures, between thermal and structural interactions in nuclear plants, and between control considerations and structural interactions in flexible robots. These relationships provide analytical based frameworks leading to optimization problem formulations. However, in multidisciplinary design problems, information based interactions become more critical. Many times, the relationships between different design parameters are not amenable to analytical characterization. Under such circumstances, information based interactions will provide the best integration paradigm, i.e., there is a need to model the data entities and their dependencies between design parameters originating from different design agents. The modeling of such data interactions and dependencies forms the basis for integrating the various design agents.

The relationship between playing computer or video games with mental health and social relationships among students in guidance schools, Kermanshah.

PubMed

Reshadat, S; Ghasemi, S R; Ahmadian, M; RajabiGilan, N

2014-01-09

Computer or video games are a popular recreational activity and playing them may constitute a large part of leisure time. This cross-sectional study aimed to evaluate the relationship between playing computer or video games with mental health and social relationships among students in guidance schools in Kermanshah, Islamic Republic of Iran, in 2012. Our total sample was 573 students and our tool was the General Health Questionnaire (GHQ-28) and social relationships questionnaires. Survey respondents reported spending an average of 71.07 (SD 72.1) min/day on computer or video games. There was a significant relationship between time spent playing games and general mental health (P < 0.04) and depression (P < 0.03). There was also a significant difference between playing and not playing computer or video games with social relationships and their subscales, including trans-local relationships (P < 0.0001) and association relationships (P < 0.01) among all participants. There was also a significant relationship between social relationships and time spent playing games (P < 0.02) and its dimensions, except for family relationships.

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

PubMed

Satpathy, Raghunath; Guru, R K; Behera, R; Nayak, B

2015-01-01

Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

Absorbing a Little Water: The Structural, Thermodynamic, and Kinetic Relationship between Pyrogallol and Its Tetarto-Hydrate

PubMed Central

2013-01-01

The anhydrate and the stoichiometric tetarto-hydrate of pyrogallol (0.25 mol water per mol pyrogallol) are both storage stable at ambient conditions, provided that they are phase pure, with the system being at equilibrium at aw (water activity) = 0.15 at 25 °C. Structures have been derived from single crystal and powder X-ray diffraction data for the anhydrate and hydrate, respectively. It is notable that the tetarto-hydrate forms a tetragonal structure with water in channels, a framework that although stabilized by water, is found as a higher energy structure on a computationally generated crystal energy landscape, which has the anhydrate crystal structure as the most stable form. Thus, a combination of slurry experiments, X-ray diffraction, spectroscopy, moisture (de)sorption, and thermo-analytical methods with the computationally generated crystal energy landscape and lattice energy calculations provides a consistent picture of the finely balanced hydration behavior of pyrogallol. In addition, two monotropically related dimethyl sulfoxide monosolvates were found in the accompanying solid form screen. PMID:24027438

Absorbing a Little Water: The Structural, Thermodynamic, and Kinetic Relationship between Pyrogallol and Its Tetarto-Hydrate.

PubMed

Braun, Doris E; Bhardwaj, Rajni M; Arlin, Jean-Baptiste; Florence, Alastair J; Kahlenberg, Volker; Griesser, Ulrich J; Tocher, Derek A; Price, Sarah L

2013-09-04

The anhydrate and the stoichiometric tetarto-hydrate of pyrogallol (0.25 mol water per mol pyrogallol) are both storage stable at ambient conditions, provided that they are phase pure, with the system being at equilibrium at a w (water activity) = 0.15 at 25 °C. Structures have been derived from single crystal and powder X-ray diffraction data for the anhydrate and hydrate, respectively. It is notable that the tetarto-hydrate forms a tetragonal structure with water in channels, a framework that although stabilized by water, is found as a higher energy structure on a computationally generated crystal energy landscape, which has the anhydrate crystal structure as the most stable form. Thus, a combination of slurry experiments, X-ray diffraction, spectroscopy, moisture (de)sorption, and thermo-analytical methods with the computationally generated crystal energy landscape and lattice energy calculations provides a consistent picture of the finely balanced hydration behavior of pyrogallol. In addition, two monotropically related dimethyl sulfoxide monosolvates were found in the accompanying solid form screen.

Computational study of β-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility.

PubMed

Kulik, Natallia; Slámová, Kristýna; Ettrich, Rüdiger; Křen, Vladimír

2015-01-28

β-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum β-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest. Computational methods including homology modeling and molecular dynamics simulations were applied to shad light on the structure-activity relationship in the enzyme. Primary sequence analysis revealed some variable regions able to influence difference in substrate affinity of hexosaminidases. Moreover, docking in combination with consequent molecular dynamics simulations of C-6 modified glycosides enabled us to identify the structural features required for accommodation and processing of these bulky substrates in the active site of hexosaminidase from T. flavus. To access the reliability of predictions on basis of the reported model, all results were confronted with available experimental data that demonstrated the principal correctness of the predictions as well as the model. The main variable regions in β-N-acetylhexosaminidases determining difference in modified substrate affinity are located close to the active site entrance and engage two loops. Differences in primary sequence and the spatial arrangement of these loops and their interplay with active site amino acids, reflected by interaction energies and dynamics, account for the different catalytic activity and substrate specificity of the various fungal and bacterial β-N-acetylhexosaminidases.

Computational study of the structure-free radical scavenging relationship of procyanidins.

PubMed

Mendoza-Wilson, Ana María; Castro-Arredondo, Sergio Ivan; Balandrán-Quintana, René Renato

2014-10-15

Procyanidins (PCs) are effective free radical scavengers, however, their antioxidant ability is variable because they have different degrees of polymerisation, are composed by distinct types of subunits and are very susceptible to changes in conformation. In this work the structure-free radical scavenging relationship of monomers, dimers and trimers of PCs was studied through the hydrogen atom transfer (HAT), sequential proton-loss electron-transfer (SPLET) and single electron transfer followed by proton transfer (SET-PT) mechanisms in aqueous phase, employing the Density Functional Theory (DFT) computational method. The structure-free radical scavenging relationship of PCs showed a very similar behaviour in HAT and SET-PT mechanisms, but very different in the SPLET mechanism. The structural factor that showed more effects on the ability of PCs to scavenge free radicals in aqueous phase was the conformation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Natural Phenolic Inhibitors of Trichothecene Biosynthesis by the Wheat Fungal Pathogen Fusarium culmorum: A Computational Insight into the Structure-Activity Relationship

PubMed Central

Pani, Giovanna; Dessì, Alessandro; Dallocchio, Roberto; Scherm, Barbara; Azara, Emanuela; Delogu, Giovanna

2016-01-01

A model of the trichodiene synthase (TRI5) of the wheat fungal pathogen and type-B trichothecene producer Fusarium culmorum was developed based on homology modelling with the crystallized protein of F. sporotrichioides. Eight phenolic molecules, namely ferulic acid 1, apocynin 2, propyl gallate 3, eugenol 4, Me-dehydrozingerone 5, eugenol dimer 6, magnolol 7, and ellagic acid 8, were selected for their ability to inhibit trichothecene production and/or fungal vegetative growth in F. culmorum. The chemical structures of phenols were constructed and partially optimised based on Molecular Mechanics (MM) studies and energy minimisation by Density Functional Theory (DFT). Docking analysis of the phenolic molecules was run on the 3D model of F. culmorum TRI5. Experimental biological activity, molecular descriptors and interacting-structures obtained from computational analysis were compared. Besides the catalytic domain, three privileged sites in the interaction with the inhibitory molecules were identified on the protein surface. The TRI5-ligand interactions highlighted in this study represent a powerful tool to the identification of new Fusarium-targeted molecules with potential as trichothecene inhibitors. PMID:27294666

A Combination of Hand-Held Models and Computer Imaging Programs Helps Students Answer Oral Questions about Molecular Structure and Function: A Controlled Investigation of Student Learning

ERIC Educational Resources Information Center

Harris, Michelle A.; Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Neto, Elias Chaibub; Kallio, Julie

2009-01-01

We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging…

A comprehensive analysis of the thermodynamic events involved in ligand receptor binding using CoRIA and its variants

NASA Astrophysics Data System (ADS)

Verma, Jitender; Khedkar, Vijay M.; Prabhu, Arati S.; Khedkar, Santosh A.; Malde, Alpeshkumar K.; Coutinho, Evans C.

2008-02-01

Quantitative Structure-Activity Relationships (QSAR) are being used since decades for prediction of biological activity, lead optimization, classification, identification and explanation of the mechanisms of drug action, and prediction of novel structural leads in drug discovery. Though the technique has lived up to its expectations in many aspects, much work still needs to be done in relation to problems related to the rational design of peptides. Peptides are the drugs of choice in many situations, however, designing them rationally is a complicated task and the complexity increases with the length of their sequence. In order to deal with the problem of peptide optimization, one of our recently developed QSAR formalisms CoRIA (Comparative Residue Interaction Analysis) is being expanded and modified as: reverse-CoRIA ( rCoRIA) and mixed-CoRIA ( mCoRIA) approaches. In these methodologies, the peptide is fragmented into individual units and the interaction energies (van der Waals, Coulombic and hydrophobic) of each amino acid in the peptide with the receptor as a whole ( rCoRIA) and with individual active site residues in the receptor ( mCoRIA) are calculated, which along with other thermodynamic descriptors, are used as independent variables that are correlated to the biological activity by chemometric methods. As a test case, the three CoRIA methodologies have been validated on a dataset of diverse nonamer peptides that bind to the Class I major histocompatibility complex molecule HLA-A*0201, and for which some structure activity relationships have already been reported. The different models developed, and validated both internally as well as externally, were found to be robust with statistically significant values of r 2 (correlation coefficient) and r 2 pred (predictive r 2). These models were able to identify all the structure activity relationships known for this class of peptides, as well uncover some new relationships. This means that these methodologies will perform well for other peptide datasets too. The major advantage of these approaches is that they explicitly utilize the 3D structures of small molecules or peptides as well as their macromolecular targets, to extract position-specific information about important interactions between the ligand and receptor, which can assist the medicinal and computational chemists in designing new molecules, and biologists in studying the influence of mutations in the target receptor on ligand binding.

The Effect of Emphasizing Mathematical Structure in the Acquisition of Whole Number Computation Skills (Addition and Subtraction) By Seven- and Eight-Year Olds: A Clinical Investigation.

ERIC Educational Resources Information Center

Uprichard, A. Edward; Collura, Carolyn

This investigation sought to determine the effect of emphasizing mathematical structure in the acquisition of computational skills by seven- and eight-year-olds. The meaningful development-of-structure approach emphasized closure, commutativity, associativity, and the identity element of addition; the inverse relationship between addition and…

The effects of a visualization-centered curriculum on conceptual understanding and representational competence in high school biology

NASA Astrophysics Data System (ADS)

Wilder, Anna

The purpose of this study was to investigate the effects of a visualization-centered curriculum, Hemoglobin: A Case of Double Identity, on conceptual understanding and representational competence in high school biology. Sixty-nine students enrolled in three sections of freshman biology taught by the same teacher participated in this study. Online Chemscape Chime computer-based molecular visualizations were incorporated into the 10-week curriculum to introduce students to fundamental structure and function relationships. Measures used in this study included a Hemoglobin Structure and Function Test, Mental Imagery Questionnaire, Exam Difficulty Survey, the Student Assessment of Learning Gains, the Group Assessment of Logical Thinking, the Attitude Toward Science in School Assessment, audiotapes of student interviews, students' artifacts, weekly unit activity surveys, informal researcher observations and a teacher's weekly questionnaire. The Hemoglobin Structure and Function Test, consisting of Parts A and B, was administered as a pre and posttest. Part A used exclusively verbal test items to measure conceptual understanding, while Part B used visual-verbal test items to measure conceptual understanding and representational competence. Results of the Hemoglobin Structure and Function pre and posttest revealed statistically significant gains in conceptual understanding and representational competence, suggesting the visualization-centered curriculum implemented in this study was effective in supporting positive learning outcomes. The large positive correlation between posttest results on Part A, comprised of all-verbal test items, and Part B, using visual-verbal test items, suggests this curriculum supported students' mutual development of conceptual understanding and representational competence. Evidence based on student interviews, Student Assessment of Learning Gains ratings and weekly activity surveys indicated positive attitudes toward the use of Chemscape Chime software and the computer-based molecular visualization activities as learning tools. Evidence from these same sources also indicated that students felt computer-based molecular visualization activities in conjunction with other classroom activities supported their learning. Implications for instructional design are discussed.

Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable Missing Data

ERIC Educational Resources Information Center

Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K.

2003-01-01

The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…

Cortical thickness as a contributor to abnormal oscillations in schizophrenia?

PubMed

Edgar, J Christopher; Chen, Yu-Han; Lanza, Matthew; Howell, Breannan; Chow, Vivian Y; Heiken, Kory; Liu, Song; Wootton, Cassandra; Hunter, Michael A; Huang, Mingxiong; Miller, Gregory A; Cañive, José M

2014-01-01

Although brain rhythms depend on brain structure (e.g., gray and white matter), to our knowledge associations between brain oscillations and structure have not been investigated in healthy controls (HC) or in individuals with schizophrenia (SZ). Observing function-structure relationships, for example establishing an association between brain oscillations (defined in terms of amplitude or phase) and cortical gray matter, might inform models on the origins of psychosis. Given evidence of functional and structural abnormalities in primary/secondary auditory regions in SZ, the present study examined how superior temporal gyrus (STG) structure relates to auditory STG low-frequency and 40 Hz steady-state activity. Given changes in brain activity as a function of age, age-related associations in STG oscillatory activity were also examined. Thirty-nine individuals with SZ and 29 HC were recruited. 40 Hz amplitude-modulated tones of 1 s duration were presented. MEG and T1-weighted sMRI data were obtained. Using the sources localizing 40 Hz evoked steady-state activity (300 to 950 ms), left and right STG total power and inter-trial coherence were computed. Time-frequency group differences and associations with STG structure and age were also examined. Decreased total power and inter-trial coherence in SZ were observed in the left STG for initial post-stimulus low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms). Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ. Left STG post-stimulus low-frequency and 40 Hz total power were positively associated with age, again only in controls. Left STG low-frequency and steady-state gamma abnormalities distinguish SZ and HC. Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG gamma-band function-structure relationships observed in controls.

Effect of Substitution on the Aniline Moiety of the GPR88 Agonist 2-PCCA: Synthesis, Structure-Activity Relationships, and Molecular Modeling Studies.

PubMed

Jin, Chunyang; Decker, Ann M; Harris, Danni L; Blough, Bruce E

2016-10-19

GPR88, an orphan receptor richly expressed in the striatum, is implicated in a number of basal ganglia-associated disorders. In order to elucidate the functions of GPR88, an in vivo probe appropriate for CNS investigation is required. We previously reported that 2-PCCA was able to modulate GPR88-mediated cAMP production through a Gα i -coupled pathway. Early structure-activity relationship (SAR) studies suggested that the aniline moiety of 2-PCCA is a suitable site for diverse modifications. Aimed at elucidating structural requirements in this region, we have designed and synthesized a series of analogues bearing a variety of substituents at the phenyl ring of the aniline moiety. Several compounds (e.g., 5j, 5o) showed improved or comparable potency, but have lower lipophilicity than 2-PCCA (clogP 6.19). These compounds provide the basis for further optimization to probe GPR88 in vivo functions. Computational studies confirmed the SAR trends and supported the notion that 4'-substituents on the biphenyl ring exit through a largely hydrophobic binding site to the extracellular loop.

Substrate Tunnels in Enzymes: Structure-Function Relationships and Computational Methodology

PubMed Central

Kingsley, Laura J.; Lill, Markus A.

2015-01-01

In enzymes, the active site is the location where incoming substrates are chemically converted to products. In some enzymes, this site is deeply buried within the core of the protein and in order to access the active site, substrates must pass through the body of the protein via a tunnel. In many systems, these tunnels act as filters and have been found to influence both substrate specificity and catalytic mechanism. Identifying and understanding how these tunnels exert such control has been of growing interest over the past several years due to implications in fields such as protein engineering and drug design. This growing interest has spurred the development of several computational methods to identify and analyze tunnels and how ligands migrate through these tunnels. The goal of this review is to outline how tunnels influence substrate specificity and catalytic efficiency in enzymes with tunnels and to provide a brief summary of the computational tools used to identify and evaluate these tunnels. PMID:25663659

THE PRACTICE OF STRUCTURE ACTIVITY RELATIONSHIPS (SAR) IN TOXICOLOGY

EPA Science Inventory

Both qualitative and quantitative modeling methods relating chemical structure to biological activity, called structure-activity relationship analyses or SAR, are applied to the prediction and characterization of chemical toxicity. This minireview will discuss some generic issue...

MS/MS fragmentation-guided search of TMG-chitooligomycins and their structure-activity relationship in specific β-N-acetylglucosaminidase inhibition.

PubMed

Usuki, Hirokazu; Yamamoto, Yukihiro; Kumagai, Yuya; Nitoda, Teruhiko; Kanzaki, Hiroshi; Hatanaka, Tadashi

2011-04-21

The reducing tetrasaccharide TMG-chitotriomycin (1) is an inhibitor of β-N-acetylglucosaminidase (GlcNAcase), produced by the actinomycete Streptomyces anulatus NBRC13369. The inhibitor shows a unique inhibitory spectrum, that is, selectivity toward enzymes from chitin-containing organisms such as insects and fungi. Nevertheless, its structure-selectivity relationship remains to be clarified. In this study, we conducted a structure-guided search of analogues of 1 in order to obtain diverse N,N,N-trimethylglucosaminium (TMG)-containing chitooligosaccharides. In this approach, the specific fragmentation profile of 1 on ESI-MS/MS analysis was used for the selective detection of desired compounds. As a result, two new analogues, named TMG-chitomonomycin (3) and TMG-chitobiomycin (2), were obtained from a culture filtrate of 1-producing Streptomyces. Their enzyme-inhibiting activity revealed that the potency and selectivity depended on the degree of polymerization of the reducing end GlcNAc units. Furthermore, a computational modeling study inspired the inhibitory mechanism of TMG-related compounds as a mimic of the substrate in the Michaelis complex of the GH20 enzyme. This study is an example of the successful application of a MS/MS experiment for structure-guided isolation of natural products.

Adsorption Behavior, Thermodynamics, and Kinetics of the Methanol Decomposition Reaction on defective graphene-supported Pt13

NASA Astrophysics Data System (ADS)

Gasper, Raymond; Ramasubramaniam, Ashwin

Defective graphene has been shown experimentally to be an excellent support for transition-metal electrocatalysts in direct methanol fuel cells. Prior computational modeling has shown that the improved catalytic activity of graphene-supported metal clusters is in part due to increased resistance to catalyst sintering and CO poisoning, but the increased reaction rate for the methanol decomposition reaction (MDR) is not yet fully explained. Using DFT, we investigate the adsorption of MDR intermediates and reaction thermodynamics on defective graphene-supported Pt13 nanoclusters with realistic, low-symmetry morphologies. We find that the support-induced shifts in Pt13 electronic structure correlate well with a rigid shift in adsorption of MDR intermediates, and that adsorption energy scaling relationships perform well on the low-symmetry surface. We investigate the reaction kinetics and thermodynamics, including testing the effectiveness of scaling relationships for predicting reaction barriers on the nanoclusters. Using these fundamental data, we perform microkinetic modeling to quantify the effect of the support on the MDR, and to understand how the support influences surface coverages, CO poisoning, and the relationships between reaction pathways. Funded by U.S. Department of Energy under Award Number DE-SC0010610. Computational resources were provided by National Energy Research Scientific Computing Center.

Differences in TV Viewing and Computer Game Playing's Relationships with Physical Activity and Eating Behaviors among Adolescents: An NHANES Study

ERIC Educational Resources Information Center

Jashinsky, Jared; Gay, Jennifer; Hansen, Nathan; Muilenburg, Jessica

2017-01-01

Background: TV viewing and computer game use may both limit physical activity, but only TV viewing may promote a poorer diet due to exposure to food advertising and availability of the hands for snacking. Purpose: The purpose of this study was to investigate relationships between the different screen times and type 2 diabetes markers among youth.…

The Relationship of Computer Games and Reported Anger in Young People

ERIC Educational Resources Information Center

Demirok, Mukaddes; Ozdamli, Fezile; Hursen, Cigdem; Ozcinar, Zehra; Kutguner, Muge; Uzunboylu, Huseyin

2012-01-01

Playing computer games is a routine activity for most young people today. The aim of this study was to examine the relationship of time spent playing computer games, the violence of the game, and self-reported anger of students in North Cyprus. Four hundred participants between the ages of 15-18 completed the State-Trait Anger and the Anger…

A brief overview of computational structures technology related activities at NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.

1992-01-01

The presentation gives a partial overview of research and development underway in the Structures Division of LeRC, which collectively is referred to as the Computational Structures Technology Program. The activities in the program are diverse and encompass four major categories: (1) composite materials and structures; (2) probabilistic analysis and reliability; (3) design optimization and expert systems; and (4) computational methods and simulation. The approach of the program is comprehensive and entails exploration of fundamental theories of structural mechanics to accurately represent the complex physics governing engine structural performance, formulation, and implementation of computational techniques and integrated simulation strategies to provide accurate and efficient solutions of the governing theoretical models by exploiting the emerging advances in computer technology, and validation and verification through numerical and experimental tests to establish confidence and define the qualities and limitations of the resulting theoretical models and computational solutions. The program comprises both in-house and sponsored research activities. The remainder of the presentation provides a sample of activities to illustrate the breadth and depth of the program and to demonstrate the accomplishments and benefits that have resulted.

Quantitative structure-antifungal activity relationships of some benzohydrazides against Botrytis cinerea.

PubMed

Reino, José L; Saiz-Urra, Liane; Hernandez-Galan, Rosario; Aran, Vicente J; Hitchcock, Peter B; Hanson, James R; Gonzalez, Maykel Perez; Collado, Isidro G

2007-06-27

Fourteen benzohydrazides have been synthesized and evaluated for their in vitro antifungal activity against the phytopathogenic fungus Botrytis cinerea. The best antifungal activity was observed for the N',N'-dibenzylbenzohydrazides 3b-d and for the N-aminoisoindoline-derived benzohydrazide 5. A quantitative structure-activity relationship (QSAR) study has been developed using a topological substructural molecular design (TOPS-MODE) approach to interpret the antifungal activity of these synthetic compounds. The model described 98.3% of the experimental variance, with a standard deviation of 4.02. The influence of an ortho substituent on the conformation of the benzohydrazides was investigated by X-ray crystallography and supported by QSAR study. Several aspects of the structure-activity relationships are discussed in terms of the contribution of different bonds to the antifungal activity, thereby making the relationships between structure and biological activity more transparent.

Chemical space visualization: transforming multidimensional chemical spaces into similarity-based molecular networks.

PubMed

de la Vega de León, Antonio; Bajorath, Jürgen

2016-09-01

The concept of chemical space is of fundamental relevance for medicinal chemistry and chemical informatics. Multidimensional chemical space representations are coordinate-based. Chemical space networks (CSNs) have been introduced as a coordinate-free representation. A computational approach is presented for the transformation of multidimensional chemical space into CSNs. The design of transformation CSNs (TRANS-CSNs) is based upon a similarity function that directly reflects distance relationships in original multidimensional space. TRANS-CSNs provide an immediate visualization of coordinate-based chemical space and do not require the use of dimensionality reduction techniques. At low network density, TRANS-CSNs are readily interpretable and make it possible to evaluate structure-activity relationship information originating from multidimensional chemical space.

Comparative Bioinformatic Analysis of Active Site Structures in Evolutionarily Remote Homologues of α,β-Hydrolase Superfamily Enzymes.

PubMed

Suplatov, D A; Arzhanik, V K; Svedas, V K

2011-01-01

Comparative bioinformatic analysis is the cornerstone of the study of enzymes' structure-function relationship. However, numerous enzymes that derive from a common ancestor and have undergone substantial functional alterations during natural selection appear not to have a sequence similarity acceptable for a statistically reliable comparative analysis. At the same time, their active site structures, in general, can be conserved, while other parts may largely differ. Therefore, it sounds both plausible and appealing to implement a comparative analysis of the most functionally important structural elements - the active site structures; that is, the amino acid residues involved in substrate binding and the catalytic mechanism. A computer algorithm has been developed to create a library of enzyme active site structures based on the use of the PDB database, together with programs of structural analysis and identification of functionally important amino acid residues and cavities in the enzyme structure. The proposed methodology has been used to compare some α,β-hydrolase superfamily enzymes. The insight has revealed a high structural similarity of catalytic site areas, including the conservative organization of a catalytic triad and oxyanion hole residues, despite the wide functional diversity among the remote homologues compared. The methodology can be used to compare the structural organization of the catalytic and substrate binding sites of various classes of enzymes, as well as study enzymes' evolution and to create of a databank of enzyme active site structures.

Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

NASA Astrophysics Data System (ADS)

Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-12-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations.

PubMed

Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-01-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

Nonparametric regression applied to quantitative structure-activity relationships

PubMed

Constans; Hirst

2000-03-01

Several nonparametric regressors have been applied to modeling quantitative structure-activity relationship (QSAR) data. The simplest regressor, the Nadaraya-Watson, was assessed in a genuine multivariate setting. Other regressors, the local linear and the shifted Nadaraya-Watson, were implemented within additive models--a computationally more expedient approach, better suited for low-density designs. Performances were benchmarked against the nonlinear method of smoothing splines. A linear reference point was provided by multilinear regression (MLR). Variable selection was explored using systematic combinations of different variables and combinations of principal components. For the data set examined, 47 inhibitors of dopamine beta-hydroxylase, the additive nonparametric regressors have greater predictive accuracy (as measured by the mean absolute error of the predictions or the Pearson correlation in cross-validation trails) than MLR. The use of principal components did not improve the performance of the nonparametric regressors over use of the original descriptors, since the original descriptors are not strongly correlated. It remains to be seen if the nonparametric regressors can be successfully coupled with better variable selection and dimensionality reduction in the context of high-dimensional QSARs.

Exploring the binding mechanism of Heteroaryldihydropyrimidines and Hepatitis B Virus capsid combined 3D-QSAR and molecular dynamics.

PubMed

Tu, Jing; Li, Jiao Jiao; Shan, Zhi Jie; Zhai, Hong Lin

2017-01-01

The non-nucleoside drugs have been developed to treat HBV infection owing to their increased efficacy and lesser side effects, in which heteroaryldihydropyrimidines (HAPs) have been identified as effective inhibitors of HBV capsid. In this paper, the binding mechanism of HAPs targeting on HBV capsid protein was explored through three-dimensional quantitative structure-activity relationship, molecular dynamics and binding free energy decompositions. The obtained models of comparative molecular field analysis and comparative molecular similarity indices analysis enable the sufficient interpretation of structure-activity relationship of HAPs-HBV. The binding free energy analysis correlates with the experimental data. The computational results disclose that the non-polar contribution is the major driving force and Y132A mutation enhances the binding affinity for inhibitor 2 bound to HBV. The hydrogen bond interactions between the inhibitors and Trp102 help to stabilize the conformation of HAPs-HBV. The study provides insight into the binding mechanism of HAPs-HBV and would be useful for the rational design and modification of new lead compounds of HAP drugs. Copyright © 2016 Elsevier B.V. All rights reserved.

Molecular modeling studies of novel retro-binding tripeptide active-site inhibitors of thrombin.

PubMed

Lau, W F; Tabernero, L; Sack, J S; Iwanowicz, E J

1995-08-01

A novel series of retro-binding tripeptide thrombin active-site inhibitors was recently developed (Iwanowicz, E. I. et al. J. Med. Chem. 1994, 37, 2111(1)). It was hypothesized that the binding mode for these inhibitors is similar to that of the first three N-terminal residues of hirudin. This binding hypothesis was subsequently verified when the crystal structure of a member of this series, BMS-183,507 (N-[N-[N-[4-(Aminoiminomethyl)amino[-1-oxobutyl]-L- phenylalanyl]-L-allo-threonyl]-L-phenylalanine, methyl ester), was determined (Taberno, L.J. Mol. Biol. 1995, 246, 14). The methodology for developing the binding models of these inhibitors, the structure-activity relationships (SAR) and modeling studies that led to the elucidation of the proposed binding mode is described. The crystal structure of BMS-183,507/human alpha-thrombin is compared with the crystal structure of hirudin/human alpha-thrombin (Rydel, T.J. et al. Science 1990, 249,227; Rydel, T.J. et al. J. Mol Biol. 1991, 221, 583; Grutter, M.G. et al. EMBO J. 1990, 9, 2361) and with the computational binding model of BMS-183,507.

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Structure-activity relationships for skin sensitization: recent improvements to Derek for Windows.

PubMed

Langton, Kate; Patlewicz, Grace Y; Long, Anthony; Marchant, Carol A; Basketter, David A

2006-12-01

Derek for Windows (DfW) is a knowledge-based expert system that predicts the toxicity of a chemical from its structure. Its predictions are based in part on alerts that describe structural features or toxicophores associated with toxicity. Recently, improvements have been made to skin sensitization alerts within the DfW knowledge base in collaboration with Unilever. These include modifications to the alerts describing the skin sensitization potential of aldehydes, 1,2-diketones, and isothiazolinones and consist of enhancements to the toxicophore definition, the mechanistic classification, and the extent of supporting evidence provided. The outcomes from this collaboration demonstrate the importance of updating and refining computer models for the prediction of skin sensitization as new information from experimental and theoretical studies becomes available.

Redox biotransformation and delivery of anthracycline anticancer antibiotics: How interpretable structure-activity relationships of lethality using electrophilicity and the London formula for dispersion interaction work.

PubMed

Pang, Siu-Kwong

2017-03-30

Quantum chemical methods and molecular mechanics approaches face a lot of challenges in drug metabolism study because of their either insufficient accuracy or huge computational cost, or lack of clear molecular level pictures for building computational models. Low-cost QSAR methods can often be carried out even though molecular level pictures are not well defined; however, they show difficulty in identifying the mechanisms of drug metabolism and delineating the effects of chemical structures on drug toxicity because a certain amount of molecular descriptors are difficult to be interpreted. In order to make a breakthrough, it was proposed that mechanistically interpretable molecular descriptors were used to correlate with biological activity to establish structure-activity plots. The mechanistically interpretable molecular descriptors used in this study include electrophilicity and the mathematical function in the London formula for dispersion interaction, and they were calculated using quantum chemical methods. The biological activity is the lethality of anthracycline anticancer antibiotics denoted as log LD50, which were obtained by intraperitoneal injection into mice. The results reveal that the plots for electrophilicity, which can be interpreted as redox reactivity of anthracyclines, can describe oxidative degradation for detoxification and reductive bioactivation for toxicity induction. The plots for the dispersion interaction function, which represent the attraction between anthracyclines and biomolecules, can describe efflux from and influx into target cells of toxicity. The plots can also identify three structural scaffolds of anthracyclines that have different metabolic pathways, resulting in their different toxicity behavior. This structure-dependent toxicity behavior revealed in the plots can provide perspectives on design of anthracycline anticancer antibiotics. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Efficiently mapping structure-property relationships of gas adsorption in porous materials: application to Xe adsorption.

PubMed

Kaija, A R; Wilmer, C E

2017-09-08

Designing better porous materials for gas storage or separations applications frequently leverages known structure-property relationships. Reliable structure-property relationships, however, only reveal themselves when adsorption data on many porous materials are aggregated and compared. Gathering enough data experimentally is prohibitively time consuming, and even approaches based on large-scale computer simulations face challenges. Brute force computational screening approaches that do not efficiently sample the space of porous materials may be ineffective when the number of possible materials is too large. Here we describe a general and efficient computational method for mapping structure-property spaces of porous materials that can be useful for adsorption related applications. We describe an algorithm that generates random porous "pseudomaterials", for which we calculate structural characteristics (e.g., surface area, pore size and void fraction) and also gas adsorption properties via molecular simulations. Here we chose to focus on void fraction and Xe adsorption at 1 bar, 5 bar, and 10 bar. The algorithm then identifies pseudomaterials with rare combinations of void fraction and Xe adsorption and mutates them to generate new pseudomaterials, thereby selectively adding data only to those parts of the structure-property map that are the least explored. Use of this method can help guide the design of new porous materials for gas storage and separations applications in the future.

Daily computer usage correlated with undergraduate students' musculoskeletal symptoms.

PubMed

Chang, Che-Hsu Joe; Amick, Benjamin C; Menendez, Cammie Chaumont; Katz, Jeffrey N; Johnson, Peter W; Robertson, Michelle; Dennerlein, Jack Tigh

2007-06-01

A pilot prospective study was performed to examine the relationships between daily computer usage time and musculoskeletal symptoms on undergraduate students. For three separate 1-week study periods distributed over a semester, 27 students reported body part-specific musculoskeletal symptoms three to five times daily. Daily computer usage time for the 24-hr period preceding each symptom report was calculated from computer input device activities measured directly by software loaded on each participant's primary computer. General Estimating Equation models tested the relationships between daily computer usage and symptom reporting. Daily computer usage longer than 3 hr was significantly associated with an odds ratio 1.50 (1.01-2.25) of reporting symptoms. Odds of reporting symptoms also increased with quartiles of daily exposure. These data suggest a potential dose-response relationship between daily computer usage time and musculoskeletal symptoms.

Theoretical insights on the antioxidant activity of edaravone free radical scavengers derivatives

NASA Astrophysics Data System (ADS)

Cerón-Carrasco, José P.; Roy, Hélène M.; Cerezo, Javier; Jacquemin, Denis; Laurent, Adèle D.

2014-04-01

The prediction of antioxidant properties is not straightforward due to the complexity of the in vivo systems. Here, we use theoretical descriptors, including the potential of ionization, the electrodonating power and the spin density distribution, to characterize the antioxidant capacity of edaravone (EDV) derivatives. Our computations reveal the relationship between these parameters and their potential bioactivity as free radical scavengers. We conclude that more efficient antioxidants could be synthesized by tuning the R1 and R2 positions of the EDV structure, rather than modifying the R3 group. Such modifications might improve the antioxidant activity in neutral and deprotonated forms.

Chalcone dimethylallyltransferase from Morus nigra cell cultures. Substrate specificity studies.

PubMed

Vitali, Alberto; Giardina, Bruno; Delle Monache, Giuliano; Rocca, Filippo; Silvestrini, Andrea; Tafi, Andrea; Botta, Bruno

2004-01-16

A new prenyltransferase (PT) enzyme derived from the microsomal fractions of cell cultures of Morus nigra was shown to be able to prenylate exclusively chalcones with a 2',4'-dihydroxy substitution and the isoflavone genistein. Computational studies were performed to shed some light on the relationship between the structure of the substrate and the enzymatic activity. PT requires divalent cations, particularly Mg(2+), to be effective. The apparent K(m) values for gamma,gamma-dimethylallyldiphosphate and 2',4'-dihydroxychalcone were 63 and 142 microM, respectively. The maximum activity of the enzyme was expressed during the first 10 days of cell growth.

Grain Boundary Plane Orientation Fundamental Zones and Structure-Property Relationships

PubMed Central

Homer, Eric R.; Patala, Srikanth; Priedeman, Jonathan L.

2015-01-01

Grain boundary plane orientation is a profoundly important determinant of character in polycrystalline materials that is not well understood. This work demonstrates how boundary plane orientation fundamental zones, which capture the natural crystallographic symmetries of a grain boundary, can be used to establish structure-property relationships. Using the fundamental zone representation, trends in computed energy, excess volume at the grain boundary, and temperature-dependent mobility naturally emerge and show a strong dependence on the boundary plane orientation. Analysis of common misorientation axes even suggests broader trends of grain boundary energy as a function of misorientation angle and plane orientation. Due to the strong structure-property relationships that naturally emerge from this work, boundary plane fundamental zones are expected to simplify analysis of both computational and experimental data. This standardized representation has the potential to significantly accelerate research in the topologically complex and vast five-dimensional phase space of grain boundaries. PMID:26498715

Grain boundary plane orientation fundamental zones and structure-property relationships

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

Homer, Eric R.; Patala, Srikanth; Priedeman, Jonathan L.

2015-10-26

Grain boundary plane orientation is a profoundly important determinant of character in polycrystalline materials that is not well understood. This work demonstrates how boundary plane orientation fundamental zones, which capture the natural crystallographic symmetries of a grain boundary, can be used to establish structure-property relationships. Using the fundamental zone representation, trends in computed energy, excess volume at the grain boundary, and temperature-dependent mobility naturally emerge and show a strong dependence on the boundary plane orientation. Analysis of common misorientation axes even suggests broader trends of grain boundary energy as a function of misorientation angle and plane orientation. Due to themore » strong structure-property relationships that naturally emerge from this work, boundary plane fundamental zones are expected to simplify analysis of both computational and experimental data. This standardized representation has the potential to significantly accelerate research in the topologically complex and vast five-dimensional phase space of grain boundaries.« less

Relationship Between Orthographic-Motor Integration And Computer Use For The Production Of Creative And Well-Structured Written Text

ERIC Educational Resources Information Center

Christensen, Carol A.

2004-01-01

Background: Orthographic-motor integration refers to the way in which orthographic knowledge is integrated with fine-motor demands of handwriting. A strong relationship has shown to exist between orthographic-motor integration and students' ability to produce creative and well-structured written text (De La Paz & Graham, 1995). This…

3D-quantitative structure-activity relationship study for the design of novel enterovirus A71 3C protease inhibitors.

PubMed

Nie, Quandeng; Xu, Xiaoyi; Zhang, Qi; Ma, Yuying; Yin, Zheng; Shang, Luqing

2018-06-07

A three-dimensional quantitative structure-activity relationships model of enterovirus A71 3C protease inhibitors was constructed in this study. The protein-ligand interaction fingerprint was analyzed to generate a pharmacophore model. A predictive and reliable three-dimensional quantitative structure-activity relationships model was built based on the Flexible Alignment of AutoGPA. Moreover, three novel compounds (I-III) were designed and evaluated for their biochemical activity against 3C protease and anti-enterovirus A71 activity in vitro. III exhibited excellent inhibitory activity (IC 50 =0.031 ± 0.005 μM, EC 50 =0.036 ± 0.007 μM). Thus, this study provides a useful quantitative structure-activity relationships model to develop potent inhibitors for enterovirus A71 3C protease. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu

2015-01-01

Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

Prediction of local proximal tibial subchondral bone structural stiffness using subject-specific finite element modeling: Effect of selected density-modulus relationship.

PubMed

Nazemi, S Majid; Amini, Morteza; Kontulainen, Saija A; Milner, Jaques S; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D

2015-08-01

Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain initiation. Calculation of bone elastic moduli from image data is a basic step when constructing finite element models. However, different relationships between elastic moduli and imaged density (known as density-modulus relationships) have been reported in the literature. The objective of this study was to apply seven different trabecular-specific and two cortical-specific density-modulus relationships from the literature to finite element models of proximal tibia subchondral bone, and identify the relationship(s) that best predicted experimentally measured local subchondral structural stiffness with highest explained variance and least error. Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using published density-modulus relationships and mapped to corresponding finite element models. Proximal tibial structural stiffness values were compared to experimentally measured stiffness values from in-situ macro-indentation testing directly on the subchondral bone surface (47 indentation points). Regression lines between experimentally measured and finite element calculated stiffness had R(2) values ranging from 0.56 to 0.77. Normalized root mean squared error varied from 16.6% to 337.6%. Of the 21 evaluated density-modulus relationships in this study, Goulet combined with Snyder and Schneider or Rho appeared most appropriate for finite element modeling of local subchondral bone structural stiffness. Though, further studies are needed to optimize density-modulus relationships and improve finite element estimates of local subchondral bone structural stiffness. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sedentary Screen Time and Left Ventricular Structure and Function: the CARDIA Study

PubMed Central

Gibbs, Bethany Barone; Reis, Jared P.; Schelbert, Erik B.; Craft, Lynette L.; Sidney, Steve; Lima, Joao; Lewis, Cora E.

2013-01-01

Sedentary screen time (watching TV or using a computer) predicts cardiovascular outcomes independently from moderate and vigorous physical activity and could impact left ventricular structure and function through the adverse consequences of sedentary behavior. Purpose To determine whether sedentary screen time is associated with measures of left ventricular structure and function. Methods The Coronary Artery Risk Development in Young Adults (CARDIA) Study measured screen time by questionnaire and left ventricular structure and function by echocardiography in 2,854 black and white participants, aged 43–55 years, in 2010–2011. Generalized linear models evaluated cross-sectional trends for echocardiography measures across higher categories of screen time and adjusting for demographics, smoking, alcohol, and physical activity. Further models adjusted for potential intermediate factors (blood pressure, antihypertensive medication use, diabetes, and body mass index (BMI). Results The relationship between screen time and left ventricular mass(LVM) differed in blacks vs. whites. Among whites, higher screen time was associated with larger LVM (P<0.001), after adjustment for height, demographics, and lifestyle variables. Associations between screen time and LVM persisted when adjusting for blood pressure, antihypertensive medication use, and diabetes (P=0.008) but not with additional adjustment for BMI (P=0.503). Similar relationships were observed for screen time with LVM indexed to height2.7, relative wall thickness, and mass-to-volume ratio. Screen time was not associated with left ventricular structure among blacks or left ventricular function in either race group. Conclusions Sedentary screen time is associated with greater LVM in white adults and this relationship was largely explained by higher overall adiposity. The lack of association in blacks supports a potential qualitative difference in the cardiovascular consequences of sedentary screen-based behavior. PMID:23863618

Strong nonadditivity as a key structure-activity relationship feature: distinguishing structural changes from assay artifacts.

PubMed

Kramer, Christian; Fuchs, Julian E; Liedl, Klaus R

2015-03-23

Nonadditivity in protein-ligand affinity data represents highly instructive structure-activity relationship (SAR) features that indicate structural changes and have the potential to guide rational drug design. At the same time, nonadditivity is a challenge for both basic SAR analysis as well as many ligand-based data analysis techniques such as Free-Wilson Analysis and Matched Molecular Pair analysis, since linear substituent contribution models inherently assume additivity and thus do not work in such cases. While structural causes for nonadditivity have been analyzed anecdotally, no systematic approaches to interpret and use nonadditivity prospectively have been developed yet. In this contribution, we lay the statistical framework for systematic analysis of nonadditivity in a SAR series. First, we develop a general metric to quantify nonadditivity. Then, we demonstrate the non-negligible impact of experimental uncertainty that creates apparent nonadditivity, and we introduce techniques to handle experimental uncertainty. Finally, we analyze public SAR data sets for strong nonadditivity and use recourse to the original publications and available X-ray structures to find structural explanations for the nonadditivity observed. We find that all cases of strong nonadditivity (ΔΔpKi and ΔΔpIC50 > 2.0 log units) with sufficient structural information to generate reasonable hypothesis involve changes in binding mode. With the appropriate statistical basis, nonadditivity analysis offers a variety of new attempts for various areas in computer-aided drug design, including the validation of scoring functions and free energy perturbation approaches, binding pocket classification, and novel features in SAR analysis tools.

Composite mechanics for engine structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1987-01-01

Recent research activities and accomplishments at Lewis Research Center on composite mechanics for engine structures are summarized. The activities focused mainly on developing procedures for the computational simulation of composite intrinsic and structural behavior. The computational simulation encompasses all aspects of composite mechanics, advanced three-dimensional finite-element methods, damage tolerance, composite structural and dynamic response, and structural tailoring and optimization.

Composite mechanics for engine structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1989-01-01

Recent research activities and accomplishments at Lewis Research Center on composite mechanics for engine structures are summarized. The activities focused mainly on developing procedures for the computational simulation of composite intrinsic and structural behavior. The computational simulation encompasses all aspects of composite mechanics, advanced three-dimensional finite-element methods, damage tolerance, composite structural and dynamic response, and structural tailoring and optimization.

Computer memory management system

DOEpatents

Kirk, III, Whitson John

2002-01-01

A computer memory management system utilizing a memory structure system of "intelligent" pointers in which information related to the use status of the memory structure is designed into the pointer. Through this pointer system, The present invention provides essentially automatic memory management (often referred to as garbage collection) by allowing relationships between objects to have definite memory management behavior by use of coding protocol which describes when relationships should be maintained and when the relationships should be broken. In one aspect, the present invention system allows automatic breaking of strong links to facilitate object garbage collection, coupled with relationship adjectives which define deletion of associated objects. In another aspect, The present invention includes simple-to-use infinite undo/redo functionality in that it has the capability, through a simple function call, to undo all of the changes made to a data model since the previous `valid state` was noted.

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals.

PubMed

Bradbury, Steven P; Russom, Christine L; Ankley, Gerald T; Schultz, T Wayne; Walker, John D

2003-08-01

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Computer-aided drug design of falcipain inhibitors: virtual screening, structure-activity relationships, hydration site thermodynamics, and reactivity analysis.

PubMed

Shah, Falgun; Gut, Jiri; Legac, Jennifer; Shivakumar, Devleena; Sherman, Woody; Rosenthal, Philip J; Avery, Mitchell A

2012-03-26

Falcipains (FPs) are hemoglobinases of Plasmodium falciparum that are validated targets for the development of antimalarial chemotherapy. A combined ligand- and structure-based virtual screening of commercial databases was performed to identify structural analogs of virtual screening hits previously discovered in our laboratory. A total of 28 low micromolar inhibitors of FP-2 and FP-3 were identified and the structure-activity relationship (SAR) in each series was elaborated. The SAR of the compounds was unusually steep in some cases and could not be explained by a traditional analysis of the ligand-protein interactions (van der Waals, electrostatics, and hydrogen bonds). To gain further insights, a statistical thermodynamic analysis of explicit solvent in the ligand binding domains of FP-2 and FP-3 was carried out to understand the roles played by water molecules in binding of these inhibitors. Indeed, the energetics associated with the displacement of water molecules upon ligand binding explained some of the complex trends in the SAR. Furthermore, low potency of a subset of FP-2 inhibitors that could not be understood by the water energetics was explained in the context of poor chemical reactivity of the reactive centers of these compounds. The present study highlights the importance of considering energetic contributors to binding beyond traditional ligand-protein interactions. © 2012 American Chemical Society

Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

NASA Astrophysics Data System (ADS)

Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

2008-06-01

A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

Is scaffold hopping a reliable indicator for the ability of computational methods to identify structurally diverse active compounds?

NASA Astrophysics Data System (ADS)

Dimova, Dilyana; Bajorath, Jürgen

2017-07-01

Computational scaffold hopping aims to identify core structure replacements in active compounds. To evaluate scaffold hopping potential from a principal point of view, regardless of the computational methods that are applied, a global analysis of conventional scaffolds in analog series from compound activity classes was carried out. The majority of analog series was found to contain multiple scaffolds, thus enabling the detection of intra-series scaffold hops among closely related compounds. More than 1000 activity classes were found to contain increasing proportions of multi-scaffold analog series. Thus, using such activity classes for scaffold hopping analysis is likely to overestimate the scaffold hopping (core structure replacement) potential of computational methods, due to an abundance of artificial scaffold hops that are possible within analog series.

Perceptual organization in computer vision - A review and a proposal for a classificatory structure

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1993-01-01

The evolution of perceptual organization in biological vision, and its necessity in advanced computer vision systems, arises from the characteristic that perception, the extraction of meaning from sensory input, is an intelligent process. This is particularly so for high order organisms and, analogically, for more sophisticated computational models. The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. First, a brief history of perceptual organization research in both humans and computer vision is offered. Next, a classificatory structure in which to cast perceptual organization research to clarify both the nomenclature and the relationships among the many contributions is proposed. Thirdly, the perceptual organization work in computer vision in the context of this classificatory structure is reviewed. Finally, the array of computational techniques applied to perceptual organization problems in computer vision is surveyed.

Structure-reactivity relationships between fluorescent chromophores and antioxidant activity of grain and sweet sorghum seeds

USDA-ARS?s Scientific Manuscript database

Polyphenolic structures, such as tannins, are the putative cause of a variety of seed functions including bird/insect resistance and antioxidant activity. Structure-reactivity relationships are necessary to understand the influence of polyphenolic chromophore structures on the tannin content and fr...

PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

Riccardin C derivatives as anti-MRSA agents: structure-activity relationship of a series of hydroxylated bis(bibenzyl)s.

PubMed

Sawada, Hiromi; Okazaki, Miki; Morita, Daichi; Kuroda, Teruo; Matsuno, Kenji; Hashimoto, Yuichi; Miyachi, Hiroyuki

2012-12-15

Members of a series of macrocyclic bis(bibenzyl) riccardin-class derivatives were found to exhibit antibacterial activity towards methicillin-resistant Staphylococcus aureus (anti-MRSA activity). Structure-activity relationship (SAR) studies were conducted, focusing on the number and position of the hydroxyl groups. The minimum essential structure for anti-MRSA activity was also investigated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Lattice enumeration for inverse molecular design using the signature descriptor.

PubMed

Martin, Shawn

2012-07-23

We describe an inverse quantitative structure-activity relationship (QSAR) framework developed for the design of molecular structures with desired properties. This framework uses chemical fragments encoded with a molecular descriptor known as a signature. It solves a system of linear constrained Diophantine equations to reorganize the fragments into novel molecular structures. The method has been previously applied to problems in drug and materials design but has inherent computational limitations due to the necessity of solving the Diophantine constraints. We propose a new approach to overcome these limitations using the Fincke-Pohst algorithm for lattice enumeration. We benchmark the new approach against previous results on LFA-1/ICAM-1 inhibitory peptides, linear homopolymers, and hydrofluoroether foam blowing agents. Software implementing the new approach is available at www.cs.otago.ac.nz/homepages/smartin.

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations.

PubMed

Ramasubramanian, Smiruthi; Rudy, Yoram

2018-06-05

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Cortical thickness as a contributor to abnormal oscillations in schizophrenia?☆

PubMed Central

Edgar, J. Christopher; Chen, Yu-Han; Lanza, Matthew; Howell, Breannan; Chow, Vivian Y.; Heiken, Kory; Liu, Song; Wootton, Cassandra; Hunter, Michael A.; Huang, Mingxiong; Miller, Gregory A.; Cañive, José M.

2013-01-01

Introduction Although brain rhythms depend on brain structure (e.g., gray and white matter), to our knowledge associations between brain oscillations and structure have not been investigated in healthy controls (HC) or in individuals with schizophrenia (SZ). Observing function–structure relationships, for example establishing an association between brain oscillations (defined in terms of amplitude or phase) and cortical gray matter, might inform models on the origins of psychosis. Given evidence of functional and structural abnormalities in primary/secondary auditory regions in SZ, the present study examined how superior temporal gyrus (STG) structure relates to auditory STG low-frequency and 40 Hz steady-state activity. Given changes in brain activity as a function of age, age-related associations in STG oscillatory activity were also examined. Methods Thirty-nine individuals with SZ and 29 HC were recruited. 40 Hz amplitude-modulated tones of 1 s duration were presented. MEG and T1-weighted sMRI data were obtained. Using the sources localizing 40 Hz evoked steady-state activity (300 to 950 ms), left and right STG total power and inter-trial coherence were computed. Time–frequency group differences and associations with STG structure and age were also examined. Results Decreased total power and inter-trial coherence in SZ were observed in the left STG for initial post-stimulus low-frequency activity (~ 50 to 200 ms, ~ 4 to 16 Hz) as well as 40 Hz steady-state activity (~ 400 to 1000 ms). Left STG 40 Hz total power and inter-trial coherence were positively associated with left STG cortical thickness in HC, not in SZ. Left STG post-stimulus low-frequency and 40 Hz total power were positively associated with age, again only in controls. Discussion Left STG low-frequency and steady-state gamma abnormalities distinguish SZ and HC. Disease-associated damage to STG gray matter in schizophrenia may disrupt the age-related left STG gamma-band function–structure relationships observed in controls. PMID:24371794

Tetrahydrocarbazoles are a novel class of potent P-type ATPase inhibitors with antifungal activity

PubMed Central

Bublitz, Maike; Kjellerup, Lasse; Cohrt, Karen O’Hanlon; Gordon, Sandra; Mortensen, Anne Louise; Clausen, Johannes D.; Pallin, Thomas David; Hansen, John Bondo; Fuglsang, Anja Thoe; Dalby-Brown, William

2018-01-01

We have identified a series of tetrahydrocarbazoles as novel P-type ATPase inhibitors. Using a set of rationally designed analogues, we have analyzed their structure-activity relationship using functional assays, crystallographic data and computational modeling. We found that tetrahydrocarbazoles inhibit adenosine triphosphate (ATP) hydrolysis of the fungal H+-ATPase, depolarize the fungal plasma membrane and exhibit broad-spectrum antifungal activity. Comparative inhibition studies indicate that many tetrahydrocarbazoles also inhibit the mammalian Ca2+-ATPase (SERCA) and Na+,K+-ATPase with an even higher potency than Pma1. We have located the binding site for this compound class by crystallographic structure determination of a SERCA-tetrahydrocarbazole complex to 3.0 Å resolution, finding that the compound binds to a region above the ion inlet channel of the ATPase. A homology model of the Candida albicans H+-ATPase based on this crystal structure, indicates that the compounds could bind to the same pocket and identifies pocket extensions that could be exploited for selectivity enhancement. The results of this study will aid further optimization towards selective H+-ATPase inhibitors as a new class of antifungal agents. PMID:29293507

Forecasting the Environmental Impacts of New Energetic Materials

DTIC Science & Technology

2010-11-30

Quantitative structure- activity relationships for chemical reductions of organic contaminants. Environmental Toxicology and Chemistry 22(8): 1733-1742. QSARs ...activity relationships [ QSARs ]) and the use of these properties to predict the chemical?s fate with multimedia assessment models. SERDP has recently...has several parts, including the prediction of chemical properties (e.g., with quantitative structure-activity relationships [ QSARs ]) and the use of

Molecular design and structure--activity relationships leading to the potent, selective, and orally active thrombin active site inhibitor BMS-189664.

PubMed

Das, Jagabandhu; Kimball, S David; Hall, Steven E; Han, Wen Ching; Iwanowicz, Edwin; Lin, James; Moquin, Robert V; Reid, Joyce A; Sack, John S; Malley, Mary F; Chang, Chiehying Y; Chong, Saeho; Wang-Iverson, David B; Roberts, Daniel G M; Seiler, Steven M; Schumacher, William A; Ogletree, Martin L

2002-01-07

A series of structurally novel small molecule inhibitors of human alpha-thrombin was prepared to elucidate their structure-activity relationships (SARs), selectivity and activity in vivo. BMS-189664 (3) is identified as a potent, selective, and orally active reversible inhibitor of human alpha-thrombin which is efficacious in vivo in a mouse lethality model, and at inhibiting both arterial and venous thrombosis in cynomolgus monkey models.

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.

Computational Study on Atomic Structures, Electronic Properties, and Chemical Reactions at Surfaces and Interfaces and in Biomaterials

NASA Astrophysics Data System (ADS)

Takano, Yu; Kobayashi, Nobuhiko; Morikawa, Yoshitada

2018-06-01

Through computer simulations using atomistic models, it is becoming possible to calculate the atomic structures of localized defects or dopants in semiconductors, chemically active sites in heterogeneous catalysts, nanoscale structures, and active sites in biological systems precisely. Furthermore, it is also possible to clarify physical and chemical properties possessed by these nanoscale structures such as electronic states, electronic and atomic transport properties, optical properties, and chemical reactivity. It is sometimes quite difficult to clarify these nanoscale structure-function relations experimentally and, therefore, accurate computational studies are indispensable in materials science. In this paper, we review recent studies on the relation between local structures and functions for inorganic, organic, and biological systems by using atomistic computer simulations.

A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

PubMed Central

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2016-01-01

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80%) and test sets (20%). We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non-hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68%, specificity 89, 33, and 33%, sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform. PMID:27920722

DEVELOPMENT OF STRUCTURE ACTIVITY RELATIONSHIPS FOR ASSESSING ECOLOGICAL RISKS

EPA Science Inventory

In the field of environmental toxicology, structure activity relationships (SARs) have developed as scientifically-credible tools for predicting the effects of chemicals when little or no empirical data are available.

Development, synthesis and structure-activity-relationships of inhibitors of the macrophage infectivity potentiator (Mip) proteins of Legionella pneumophila and Burkholderia pseudomallei.

PubMed

Seufert, Florian; Kuhn, Maximilian; Hein, Michael; Weiwad, Matthias; Vivoli, Mirella; Norville, Isobel H; Sarkar-Tyson, Mitali; Marshall, Laura E; Schweimer, Kristian; Bruhn, Heike; Rösch, Paul; Harmer, Nicholas J; Sotriffer, Christoph A; Holzgrabe, Ulrike

2016-11-01

The bacteria Burkholderia pseudomallei and Legionella pneumophila cause severe diseases like melioidosis and Legionnaire's disease with high mortality rates despite antibiotic treatment. Due to increasing antibiotic resistances against these and other Gram-negative bacteria, alternative therapeutical strategies are in urgent demand. As a virulence factor, the macrophage infectivity potentiator (Mip) protein constitutes an attractive target. The Mip proteins of B. pseudomallei and L. pneumophila exhibit peptidyl-prolyl cis/trans isomerase (PPIase) activity and belong to the PPIase superfamily. In previous studies, the pipecolic acid moiety proved to be a valuable scaffold for inhibiting this PPIase activity. Thus, a library of pipecolic acid derivatives was established guided by structural information and computational analyses of the binding site and possible binding modes. Stability and toxicity considerations were taken into account in iterative extensions of the library. Synthesis and evaluation of the compounds in PPIase assays resulted in highly active inhibitors. The activities can be interpreted in terms of a common binding mode obtained by docking calculations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship between chemical structure of soil organic matter and intra-aggregate pore structure: evidence from X-ray computed micro-tomography

NASA Astrophysics Data System (ADS)

Kravchenko, Alexandra; Grandy, Stuart A.

2014-05-01

Understanding chemical structure of soil organic matter (SOM) and factors that affect it are vital for gaining understanding of mechanisms of C sequestration by soil. Physical protection of C by adsorption to mineral particles and physical disconnection between C sources and microbial decomposers is now regarded as the key component of soil C sequestration. Both of the processes are greatly influenced by micro-scale structure and distribution of soil pores. However, because SOM chemical structure is typically studied in disturbed (ground and sieved) soil samples the experimental evidence of the relationships between soil pore structure and chemical structure of SOM are still scarce. Our study takes advantage of the X-ray computed micro-tomography (µ-CT) tools that enable non-destructive analysis of pore structure in intact soil samples. The objective of this study is to examine the relationship between SOM chemical structure and pore-characteristics in intact soil macro-aggregates from two contrasting long-term land uses. The two studied land use treatments are a conventionally tilled corn-soybean-wheat rotation treatment and a native succession vegetation treatment removed from agricultural use >20 years ago. The study is located in southwest Michigan, USA, on sandy-loam Typic Hapludalfs. For this study we used soil macro-aggregates 4-6 mm in size collected at 0-15 cm depth. The aggregate size was selected so as both to enable high resolution of µ-CT and to provide sufficient amount of soil for C measurements. X-ray µ-CT scanning was conducted at APS Argonne at a scanning resolution of 14 µm. Two scanned aggregates (1 per treatment) were used in this preliminary study. Each aggregate was cut into 7 "geo-referenced" sections. Analyses of pore characteristics in each section were conducted using 3DMA and ImageJ image analysis tools. SOM chemistry was analyzed using pyrolysis/gas chromatography-mass spectroscopy. Results demonstrated that the relationships between SOM chemical structure and pore characteristics differed in the aggregates of the two treatments. For example, in the agricultural treatment, the aggregate sections with prevalence of small pores had lower relative lignin abundance, while higher lignin abundances occurred in aggregate sections with more large pores. This relationship could be reflecting the low accessibility of the sections dominated by small pores to plant roots. It is interesting to note that no relationship between pores and lignin were observed in the aggregate from the native succession treatment. In the native succession aggregate we found that a larger presence of protein and N-bearing compounds was associated with sections with greater presence of 35-90 µm pores. This could be a result of fungal activities, as pores of this size constitute a primary fungal habitat and fungi are known for secreting proteins. Fewer fungi in the soil under agricultural management are likely the reason that no such relationship was observed in the aggregate from the agricultural treatment. Our preliminary results indicate that substantial spatial variability patterns in SOM chemical structure can exist even within a single macro-aggregate and that pores are likely a main driver of intra-aggregate SOM chemistry.

Structure–function relationships in single molecule rectification by N-phenylbenzamide derivatives

DOE PAGES

Koenigsmann, Christopher; Ding, Wendu; Koepf, Matthieu; ...

2016-06-30

Here, we examine structure–function relationships in a series of N-phenylbenzamide (NPBA) derivatives by using computational modeling to identify molecular structures that exhibit both rectification and good conductance together with experimental studies of bias-dependent single molecule conductance and rectification behavior using the scanning tunneling microscopy break-junction technique. From a large number of computationally screened molecular diode structures, we have identified NPBA as a promising candidate, relative to the other structures that were screened. We demonstrate experimentally that conductance and rectification are both enhanced by functionalization of the NPBA 4-carboxamido-aniline moiety with electron donating methoxy groups, and are strongly correlated with themore » energy of the conducting frontier orbital relative to the Fermi level of the gold leads used in break-junction experiments.« less

Structure–function relationships in single molecule rectification by N-phenylbenzamide derivatives

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

Koenigsmann, Christopher; Ding, Wendu; Koepf, Matthieu

Here, we examine structure–function relationships in a series of N-phenylbenzamide (NPBA) derivatives by using computational modeling to identify molecular structures that exhibit both rectification and good conductance together with experimental studies of bias-dependent single molecule conductance and rectification behavior using the scanning tunneling microscopy break-junction technique. From a large number of computationally screened molecular diode structures, we have identified NPBA as a promising candidate, relative to the other structures that were screened. We demonstrate experimentally that conductance and rectification are both enhanced by functionalization of the NPBA 4-carboxamido-aniline moiety with electron donating methoxy groups, and are strongly correlated with themore » energy of the conducting frontier orbital relative to the Fermi level of the gold leads used in break-junction experiments.« less

Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins.

PubMed

Hati, Sanchita; Bhattacharyya, Sudeep

2016-01-01

A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and simulations. In particular, modern computational tools are employed to elucidate the relationship between structure, dynamics, and function in proteins. Computer-based laboratory protocols that we introduced in three modules allow students to visualize the secondary, super-secondary, and tertiary structures of proteins, analyze non-covalent interactions in protein-ligand complexes, develop three-dimensional structural models (homology model) for new protein sequences and evaluate their structural qualities, and study proteins' intrinsic dynamics to understand their functions. In the fourth module, students are assigned to an authentic research problem, where they apply their laboratory skills (acquired in modules 1-3) to answer conceptual biophysical questions. Through this process, students gain in-depth understanding of protein dynamics-the missing link between structure and function. Additionally, the requirement of term papers sharpens students' writing and communication skills. Finally, these projects result in new findings that are communicated in peer-reviewed journals. © 2016 The International Union of Biochemistry and Molecular Biology.

Selection of molecular descriptors with artificial intelligence for the understanding of HIV-1 protease peptidomimetic inhibitors-activity.

PubMed

Sirois, S; Tsoukas, C M; Chou, Kuo-Chen; Wei, Dongqing; Boucher, C; Hatzakis, G E

2005-03-01

Quantitative Structure Activity Relationship (QSAR) techniques are used routinely by computational chemists in drug discovery and development to analyze datasets of compounds. Quantitative numerical methods like Partial Least Squares (PLS) and Artificial Neural Networks (ANN) have been used on QSAR to establish correlations between molecular properties and bioactivity. However, ANN may be advantageous over PLS because it considers the interrelations of the modeled variables. This study focused on the HIV-1 Protease (HIV-1 Pr) inhibitors belonging to the peptidomimetic class of compounds. The main objective was to select molecular descriptors with the best predictive value for antiviral potency (Ki). PLS and ANN were used to predict Ki activity of HIV-1 Pr inhibitors and the results were compared. To address the issue of dimensionality reduction, Genetic Algorithms (GA) were used for variable selection and their performance was compared against that of ANN. Finally, the structure of the optimum ANN achieving the highest Pearson's-R coefficient was determined. On the basis of Pearson's-R, PLS and ANN were compared to determine which exhibits maximum performance. Training and validation of models was performed on 15 random split sets of the master dataset consisted of 231 compounds. For each compound 192 molecular descriptors were considered. The molecular structure and constant of inhibition (Ki) were selected from the NIAID database. Study findings suggested that non-covalent interactions such as hydrophobicity, shape and hydrogen bonding describe well the antiviral activity of the HIV-1 Pr compounds. The significance of lipophilicity and relationship to HIV-1 associated hyperlipidemia and lipodystrophy syndrome warrant further investigation.

Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

PubMed Central

Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

2013-01-01

The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

QSAR modeling of GPCR ligands: methodologies and examples of applications.

PubMed

Tropsha, A; Wang, S X

2006-01-01

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

Incrementally Dissociating Syntax and Semantics

ERIC Educational Resources Information Center

Brennan, Jonathan R.

2010-01-01

A basic challenge for research into the neurobiology of language is understanding how the brain combines words to make complex representations. Linguistic theory divides this task into several computations including syntactic structure building and semantic composition. The close relationship between these computations, however, poses a strong…

Investigating the Structural Relationship for the Determinants of Cloud Computing Adoption in Education

ERIC Educational Resources Information Center

Bhatiasevi, Veera; Naglis, Michael

2016-01-01

This research is one of the first few to investigate the adoption and usage of cloud computing in higher education in the context of developing countries, in this case Thailand. It proposes extending the technology acceptance model to integrate subjective norm, perceived convenience, trust, computer self-efficacy, and software functionality in…

Categories of Computer Use and Their Relationships with Attitudes toward Computers.

ERIC Educational Resources Information Center

Mitra, Anandra

1998-01-01

Analysis of attitude and use questionnaires completed by undergraduates (n1,444) at Wake Forest University determined that computers were used most frequently for word processing. Other uses were e-mail for task and non-task activities and mathematical and statistical computation. Results suggest that the level of computer use was related to…

Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities.

PubMed

Ohtana, Yuki; Abdullah, Azian Azamimi; Altaf-Ul-Amin, Md; Huang, Ming; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Horai, Hisayuki; Nakamura, Yukiko; Morita Hirai, Aki; Lange, Klaus W; Kibinge, Nelson K; Katsuragi, Tetsuo; Shirai, Tsuyoshi; Kanaya, Shigehiko

2014-12-01

Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network-based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2-dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group-biological activity pairs. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthesis facilitates an understanding of the structural basis for translation inhibition by the lissoclimides

NASA Astrophysics Data System (ADS)

Könst, Zef A.; Szklarski, Anne R.; Pellegrino, Simone; Michalak, Sharon E.; Meyer, Mélanie; Zanette, Camila; Cencic, Regina; Nam, Sangkil; Voora, Vamsee K.; Horne, David A.; Pelletier, Jerry; Mobley, David L.; Yusupova, Gulnara; Yusupov, Marat; Vanderwal, Christopher D.

2017-11-01

The lissoclimides are unusual succinimide-containing labdane diterpenoids that were reported to be potent cytotoxins. Our short semisynthesis and analogue-oriented synthesis approaches provide a series of lissoclimide natural products and analogues that expand the structure-activity relationships (SARs) in this family. The semisynthesis approach yielded significant quantities of chlorolissoclimide (CL) to permit an evaluation against the National Cancer Institute's 60-cell line panel and allowed us to obtain an X-ray co-crystal structure of the synthetic secondary metabolite with the eukaryotic 80S ribosome. Although it shares a binding site with other imide-based natural product translation inhibitors, CL engages in a particularly interesting and novel face-on halogen-π interaction between the ligand's alkyl chloride and a guanine residue. Our analogue-oriented synthesis provides many more lissoclimide compounds, which were tested against aggressive human cancer cell lines and for protein synthesis inhibitory activity. Finally, computational modelling was used to explain the SARs of certain key compounds and set the stage for the structure-guided design of better translation inhibitors.

Predicting binding modes of reversible peptide-based inhibitors of falcipain-2 consistent with structure-activity relationships.

PubMed

Hernández González, Jorge Enrique; Hernández Alvarez, Lilian; Pascutti, Pedro Geraldo; Valiente, Pedro A

2017-09-01

Falcipain-2 (FP-2) is a major hemoglobinase of Plasmodium falciparum, considered an important drug target for the development of antimalarials. A previous study reported a novel series of 20 reversible peptide-based inhibitors of FP-2. However, the lack of tridimensional structures of the complexes hinders further optimization strategies to enhance the inhibitory activity of the compounds. Here we report the prediction of the binding modes of the aforementioned inhibitors to FP-2. A computational approach combining previous knowledge on the determinants of binding to the enzyme, docking, and postdocking refinement steps, is employed. The latter steps comprise molecular dynamics simulations and free energy calculations. Remarkably, this approach leads to the identification of near-native ligand conformations when applied to a validation set of protein-ligand structures. Overall, we proposed substrate-like binding modes of the studied compounds fulfilling the structural requirements for FP-2 binding and yielding free energy values that correlated well with the experimental data. Proteins 2017; 85:1666-1683. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

CSM Testbed Development and Large-Scale Structural Applications

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Gillian, R. E.; Mccleary, Susan L.; Lotts, C. G.; Poole, E. L.; Overman, A. L.; Macy, S. C.

1989-01-01

A research activity called Computational Structural Mechanics (CSM) conducted at the NASA Langley Research Center is described. This activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM Testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM Testbed methods development environment is presented and some new numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

Decoration of Chondroitin Polysaccharide with Threonine: Synthesis, Conformational Study, and Ice-Recrystallization Inhibition Activity.

PubMed

Laezza, Antonio; Casillo, Angela; Cosconati, Sandro; Biggs, Caroline I; Fabozzi, Antonio; Paduano, Luigi; Iadonisi, Alfonso; Novellino, Ettore; Gibson, Matthew I; Randazzo, Antonio; Corsaro, Maria M; Bedini, Emiliano

2017-08-14

Several threonine (Thr)- and alanine (Ala)-rich antifreeze glycoproteins (AFGPs) and polysaccharides act in nature as ice recrystallization inhibitors. Among them, the Thr-decorated capsular polysaccharide (CPS) from the cold-adapted Colwellia psychrerythraea 34H bacterium was recently investigated for its cryoprotectant activity. A semisynthetic mimic thereof was here prepared from microbial sourced chondroitin through a four-step strategy, involving a partial protection of the chondroitin polysaccharide as a key step for gaining an unprecedented quantitative amidation of its glucuronic acid units. In-depth NMR and computational analysis suggested a fairly linear conformation for the semisynthetic polysaccharide, for which the antifreeze activity by a quantitative ice recrystallization inhibition assay was measured. We compared the structure-activity relationships for the Thr-derivatized chondroitin and the natural Thr-decorated CPS from C. psychrerythraea.

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

Jiang, Lin; Liu, Cong; Leibly, David

Amyloid protein aggregates are associated with dozens of devastating diseases including Alzheimer’s, Parkinson’s, ALS, and diabetes type 2. While structure-based discovery of compounds has been effective in combating numerous infectious and metabolic diseases, ignorance of amyloid structure has hindered similar approaches to amyloid disease. Here we show that knowledge of the atomic structure of one of the adhesive, steric-zipper segments of the amyloid-beta (Aβ) protein of Alzheimer’s disease, when coupled with computational methods, identifies eight diverse but mainly flat compounds and three compound derivatives that reduce Aβ cytotoxicity against mammalian cells by up to 90%. Although these compounds bind tomore » Aβ fibers, they do not reduce fiber formation of Aβ. Structure-activity relationship studies of the fiber-binding compounds and their derivatives suggest that compound binding increases fiber stability and decreases fiber toxicity, perhaps by shifting the equilibrium of Aβ from oligomers to fibers.« less

Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis.

PubMed

Marshall, S J; Biddle, S J H; Gorely, T; Cameron, N; Murdey, I

2004-10-01

To review the empirical evidence of associations between television (TV) viewing, video/computer game use and (a) body fatness, and (b) physical activity. Meta-analysis. Published English-language studies were located from computerized literature searches, bibliographies of primary studies and narrative reviews, and manual searches of personal archives. Included studies presented at least one empirical association between TV viewing, video/computer game use and body fatness or physical activity among samples of children and youth aged 3-18 y. The mean sample-weighted corrected effect size (Pearson r). Based on data from 52 independent samples, the mean sample-weighted effect size between TV viewing and body fatness was 0.066 (95% CI=0.056-0.078; total N=44,707). The sample-weighted fully corrected effect size was 0.084. Based on data from six independent samples, the mean sample-weighted effect size between video/computer game use and body fatness was 0.070 (95% CI=-0.048 to 0.188; total N=1,722). The sample-weighted fully corrected effect size was 0.128. Based on data from 39 independent samples, the mean sample-weighted effect size between TV viewing and physical activity was -0.096 (95% CI=-0.080 to -0.112; total N=141,505). The sample-weighted fully corrected effect size was -0.129. Based on data from 10 independent samples, the mean sample-weighted effect size between video/computer game use and physical activity was -0.104 (95% CI=-0.080 to -0.128; total N=119,942). The sample-weighted fully corrected effect size was -0.141. A statistically significant relationship exists between TV viewing and body fatness among children and youth although it is likely to be too small to be of substantial clinical relevance. The relationship between TV viewing and physical activity is small but negative. The strength of these relationships remains virtually unchanged even after correcting for common sources of bias known to impact study outcomes. While the total amount of time per day engaged in sedentary behavior is inevitably prohibitive of physical activity, media-based inactivity may be unfairly implicated in recent epidemiologic trends of overweight and obesity among children and youth. Relationships between sedentary behavior and health are unlikely to be explained using single markers of inactivity, such as TV viewing or video/computer game use.

Applications of large-scale density functional theory in biology

NASA Astrophysics Data System (ADS)

Cole, Daniel J.; Hine, Nicholas D. M.

2016-10-01

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

Structure-activity relationship of indoloquinoline analogs anti-MRSA.

PubMed

Zhao, Min; Kamada, Tomonori; Takeuchi, Aya; Nishioka, Hiromi; Kuroda, Teruo; Takeuchi, Yasuo

2015-12-01

Indolo[3,2-b]quinoline analogs (3a-3s), 4-(acridin-9-ylamino) phenol hydrochloride (4), benzofuro[3,2-b]quinoline (3t), indeno[1,2-b]quinolines (3u and 3v) have been synthesized. Those compounds were found to exhibit anti-bacterial activity towards Methicillin-resistant Staphylococcus aureus (anti-MRSA activity). Structure-activity relationship studies were conducted that indoloquinoline ring, benzofuroquinoline ring and 4-aminophenol group are essential structure for anti-MRSA activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

Computational prediction of hinge axes in proteins

PubMed Central

2014-01-01

Background A protein's function is determined by the wide range of motions exhibited by its 3D structure. However, current experimental techniques are not able to reliably provide the level of detail required for elucidating the exact mechanisms of protein motion essential for effective drug screening and design. Computational tools are instrumental in the study of the underlying structure-function relationship. We focus on a special type of proteins called "hinge proteins" which exhibit a motion that can be interpreted as a rotation of one domain relative to another. Results This work proposes a computational approach that uses the geometric structure of a single conformation to predict the feasible motions of the protein and is founded in recent work from rigidity theory, an area of mathematics that studies flexibility properties of general structures. Given a single conformational state, our analysis predicts a relative axis of motion between two specified domains. We analyze a dataset of 19 structures known to exhibit this hinge-like behavior. For 15, the predicted axis is consistent with a motion to a second, known conformation. We present a detailed case study for three proteins whose dynamics have been well-studied in the literature: calmodulin, the LAO binding protein and the Bence-Jones protein. Conclusions Our results show that incorporating rigidity-theoretic analyses can lead to effective computational methods for understanding hinge motions in macromolecules. This initial investigation is the first step towards a new tool for probing the structure-dynamics relationship in proteins. PMID:25080829

Reliable but Timesaving: In Search of an Efficient Quantum-chemical Method for the Description of Functional Fullerenes.

PubMed

Reis, H; Rasulev, B; Papadopoulos, M G; Leszczynski, J

2015-01-01

Fullerene and its derivatives are currently one of the most intensively investigated species in the area of nanomedicine and nanochemistry. Various unique properties of fullerenes are responsible for their wide range applications in industry, biology and medicine. A large pool of functionalized C60 and C70 fullerenes is investigated theoretically at different levels of quantum-mechanical theory. The semiempirial PM6 method, density functional theory with the B3LYP functional, and correlated ab initio MP2 method are employed to compute the optimized structures, and an array of properties for the considered species. In addition to the calculations for isolated molecules, the results of solution calculations are also reported at the DFT level, using the polarizable continuum model (PCM). Ionization potentials (IPs) and electron affinities (EAs) are computed by means of Koopmans' theorem as well as with the more accurate but computationally expensive ΔSCF method. Both procedures yield comparable values, while comparison of IPs and EAs computed with different quantum-mechanical methods shows surprisingly large differences. Harmonic vibrational frequencies are computed at the PM6 and B3LYP levels of theory and compared with each other. A possible application of the frequencies as 3D descriptors in the EVA (EigenVAlues) method is shown. All the computed data are made available, and may be used to replace experimental data in routine applications where large amounts of data are required, e.g. in structure-activity relationship studies of the toxicity of fullerene derivatives.

Targeting YAP/TAZ-TEAD protein-protein interactions using fragment-based and computational modeling approaches

PubMed Central

Verma, Chandra

2017-01-01

The Hippo signaling pathway, which is implicated in the regulation of organ size, has emerged as a potential target for the development of cancer therapeutics. YAP, TAZ (transcription co-activators) and TEAD (transcription factor) are the downstream transcriptional machinery and effectors of the pathway. Formation of the YAP/TAZ-TEAD complex leads to transcription of growth-promoting genes. Conversely, disrupting the interactions of the complex decreases cell proliferation. Herein, we screened a 1000-member fragment library using Thermal Shift Assay and identified a hit fragment. We confirmed its binding at the YAP/TAZ-TEAD interface by X-ray crystallography, and showed that it occupies the same hydrophobic pocket as a conserved phenylalanine of YAP/TAZ. This hit fragment serves as a scaffold for the development of compounds that have the potential to disrupt YAP/TAZ-TEAD interactions. Structure-activity relationship studies and computational modeling were also carried out to identify more potent compounds that may bind at this validated druggable binding site. PMID:28570566

Sequence-Dependent Structure/Function Relationships of Catalytic Peptide-Enabled Gold Nanoparticles Generated under Ambient Synthetic Conditions.

PubMed

Bedford, Nicholas M; Hughes, Zak E; Tang, Zhenghua; Li, Yue; Briggs, Beverly D; Ren, Yang; Swihart, Mark T; Petkov, Valeri G; Naik, Rajesh R; Knecht, Marc R; Walsh, Tiffany R

2016-01-20

Peptide-enabled nanoparticle (NP) synthesis routes can create and/or assemble functional nanomaterials under environmentally friendly conditions, with properties dictated by complex interactions at the biotic/abiotic interface. Manipulation of this interface through sequence modification can provide the capability for material properties to be tailored to create enhanced materials for energy, catalysis, and sensing applications. Fully realizing the potential of these materials requires a comprehensive understanding of sequence-dependent structure/function relationships that is presently lacking. In this work, the atomic-scale structures of a series of peptide-capped Au NPs are determined using a combination of atomic pair distribution function analysis of high-energy X-ray diffraction data and advanced molecular dynamics (MD) simulations. The Au NPs produced with different peptide sequences exhibit varying degrees of catalytic activity for the exemplar reaction 4-nitrophenol reduction. The experimentally derived atomic-scale NP configurations reveal sequence-dependent differences in structural order at the NP surface. Replica exchange with solute-tempering MD simulations are then used to predict the morphology of the peptide overlayer on these Au NPs and identify factors determining the structure/catalytic properties relationship. We show that the amount of exposed Au surface, the underlying surface structural disorder, and the interaction strength of the peptide with the Au surface all influence catalytic performance. A simplified computational prediction of catalytic performance is developed that can potentially serve as a screening tool for future studies. Our approach provides a platform for broadening the analysis of catalytic peptide-enabled metallic NP systems, potentially allowing for the development of rational design rules for property enhancement.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

The structure-activity relationship of inhibitors of serotonin uptake and receptor binding

NASA Astrophysics Data System (ADS)

Hansch, Corwin; Caldwell, Jonathan

1991-10-01

An analysis of five different datasets of inhibitors of serotonin uptake has yielded quantitative structure/ activity relationships (QSARs) which delineate the role of steric and hydrophobic properties essential for inhibition by phenylethylamine-type analogues.

Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

EPA Science Inventory

Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

Applied Computational Chemistry for the Blind and Visually Impaired

ERIC Educational Resources Information Center

Wedler, Henry B.; Cohen, Sarah R.; Davis, Rebecca L.; Harrison, Jason G.; Siebert, Matthew R.; Willenbring, Dan; Hamann, Christian S.; Shaw, Jared T.; Tantillo, Dean J.

2012-01-01

We describe accommodations that we have made to our applied computational-theoretical chemistry laboratory to provide access for blind and visually impaired students interested in independent investigation of structure-function relationships. Our approach utilizes tactile drawings, molecular model kits, existing software, Bash and Perl scripts…

Mathematics and Computer Science: Exploring a Symbiotic Relationship

ERIC Educational Resources Information Center

Bravaco, Ralph; Simonson, Shai

2004-01-01

This paper describes a "learning community" designed for sophomore computer science majors who are simultaneously studying discrete mathematics. The learning community consists of three courses: Discrete Mathematics, Data Structures and an Integrative Seminar/Lab. The seminar functions as a link that integrates the two disciplines. Participation…

3D electron tomography of pretreated biomass informs atomic modeling of cellulose microfibrils.

PubMed

Ciesielski, Peter N; Matthews, James F; Tucker, Melvin P; Beckham, Gregg T; Crowley, Michael F; Himmel, Michael E; Donohoe, Bryon S

2013-09-24

Fundamental insights into the macromolecular architecture of plant cell walls will elucidate new structure-property relationships and facilitate optimization of catalytic processes that produce fuels and chemicals from biomass. Here we introduce computational methodology to extract nanoscale geometry of cellulose microfibrils within thermochemically treated biomass directly from electron tomographic data sets. We quantitatively compare the cell wall nanostructure in corn stover following two leading pretreatment strategies: dilute acid with iron sulfate co-catalyst and ammonia fiber expansion (AFEX). Computational analysis of the tomographic data is used to extract mathematical descriptions for longitudinal axes of cellulose microfibrils from which we calculate their nanoscale curvature. These nanostructural measurements are used to inform the construction of atomistic models that exhibit features of cellulose within real, process-relevant biomass. By computational evaluation of these atomic models, we propose relationships between the crystal structure of cellulose Iβ and the nanoscale geometry of cellulose microfibrils.

QSAR DataBank - an approach for the digital organization and archiving of QSAR model information

PubMed Central

2014-01-01

Background Research efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure–Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvious limitations when they come to effectively representing mathematical models, including complex and non-linear, and large bodies of associated numerical chemical data. It is not supportive of secondary information extraction or reuse efforts while in silico studies poses additional requirements for accessibility, transparency and reproducibility of the research. This gap can and should be bridged by introducing domain-specific digital data exchange standards and tools. The current publication presents a formal specification of the quantitative structure-activity relationship data organization and archival format called the QSAR DataBank (QsarDB for shorter, or QDB for shortest). Results The article describes QsarDB data schema, which formalizes QSAR concepts (objects and relationships between them) and QsarDB data format, which formalizes their presentation for computer systems. The utility and benefits of QsarDB have been thoroughly tested by solving everyday QSAR and predictive modeling problems, with examples in the field of predictive toxicology, and can be applied for a wide variety of other endpoints. The work is accompanied with open source reference implementation and tools. Conclusions The proposed open data, open source, and open standards design is open to public and proprietary extensions on many levels. Selected use cases exemplify the benefits of the proposed QsarDB data format. General ideas for future development are discussed. PMID:24910716

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

QSAR, DFT and molecular modeling studies of peptides from HIV-1 to describe their recognition properties by MHC-I.

PubMed

Andrade-Ochoa, S; García-Machorro, J; Bello, Martiniano; Rodríguez-Valdez, L M; Flores-Sandoval, C A; Correa-Basurto, J

2017-08-03

Human immunodeficiency virus type-1 (HIV-1) has infected more than 40 million people around the world. HIV-1 treatment still has several side effects, and the development of a vaccine, which is another potential option for decreasing human infections, has faced challenges. This work presents a computational study that includes a quantitative structure activity relationship(QSAR) using density functional theory(DFT) for reported peptides to identify the principal quantum mechanics descriptors related to peptide activity. In addition, the molecular recognition properties of these peptides are explored on major histocompatibility complex I (MHC-I) through docking and molecular dynamics (MD) simulations accompanied by the Molecular Mechanics Generalized Born Surface Area (MMGBSA) approach for correlating peptide activity reported elsewhere vs. theoretical peptide affinity. The results show that the carboxylic acid and hydroxyl groups are chemical moieties that have an inverse relationship with biological activity. The number of sulfides, pyrroles and imidazoles from the peptide structure are directly related to biological activity. In addition, the HOMO orbital energy values of the total absolute charge and the Ghose-Crippen molar refractivity of peptides are descriptors directly related to the activity and affinity on MHC-I. Docking and MD simulation studies accompanied by an MMGBSA analysis show that the binding free energy without considering the entropic contribution is energetically favorable for all the complexes. Furthermore, good peptide interaction with the most affinity is evaluated experimentally for three proteins. Overall, this study shows that the combination of quantum mechanics descriptors and molecular modeling studies could help describe the immunogenic properties of peptides from HIV-1.

Using Theoretical Descriptions in Structure Activity Relations. 3. Electronic Descriptors

DTIC Science & Technology

1988-08-01

Activity Relationships (QSAR) have been used successfully in the past to develop predictive equations for several biological and physical properties...Linear Free Energy Relationships (,FF.3) and is based on work by Hammet in which he derived electronic descriptors for the dissociation of substituted...structure of a compound and its activity in a system. Several different structural descriptors have been used in QSAR equations . These range from

MOLECULAR INTERACTION POTENTIALS FOR THE DEVELOPMENT OF STRUCTURE-ACTIVITY RELATIONSHIPS

EPA Science Inventory

Abstract
One reasonable approach to the analysis of the relationships between molecular structure and toxic activity is through the investigation of the forces and intermolecular interactions responsible for chemical toxicity. The interaction between the xenobiotic and the bio...

ESTIMATION OF CHEMICAL SPECIFIC PARAMETERS WITHIN PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC MODELS

EPA Science Inventory

While relationships between chemical structure and observed properties or activities (QSAR - quantitative structure activity relationship) can be used to predict the behavior of unknown chemicals, this method is semiempirical in nature relying on high quality experimental data to...

Multidimensional Predictors of Fatigue among Octogenarians and Centenarians

PubMed Central

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.

2012-01-01

Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445

Multidimensional predictors of fatigue among octogenarians and centenarians.

PubMed

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Woodard, J L; Tenover, J S; Siegler, I C; Rott, C; Rodgers, W L; Hausman, D; Arnold, J; Davey, A

2012-01-01

Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. Copyright © 2011 S. Karger AG, Basel.

QSAR studies in the discovery of novel type-II diabetic therapies.

PubMed

Abuhammad, Areej; Taha, Mutasem O

2016-01-01

Type-II diabetes mellitus (T2DM) is a complex chronic disease that represents a major therapeutic challenge. Despite extensive efforts in T2DM drug development, therapies remain unsatisfactory. Currently, there are many novel and important antidiabetic drug targets under investigation by many research groups worldwide. One of the main challenges to develop effective orally active hypoglycemic agents is off-target effects. Computational tools have impacted drug discovery at many levels. One of the earliest methods is quantitative structure-activity relationship (QSAR) studies. QSAR strategies help medicinal chemists understand the relationship between hypoglycemic activity and molecular properties. Hence, QSAR may hold promise in guiding the synthesis of specifically designed novel ligands that demonstrate high potency and target selectivity. This review aims to provide an overview of the QSAR strategies used to model antidiabetic agents. In particular, this review focuses on drug targets that raised recent scientific interest and/or led to successful antidiabetic agents in the market. Special emphasis has been made on studies that led to the identification of novel antidiabetic scaffolds. Computer-aided molecular design and discovery techniques like QSAR have a great potential in designing leads against complex diseases such as T2DM. Combined with other in silico techniques, QSAR can provide more useful and rational insights to facilitate the discovery of novel compounds. However, since T2DM is a complex disease that includes several faulty biological targets, multi-target QSAR studies are recommended in the future to achieve efficient antidiabetic therapies.

Sense-making for intelligence analysis on social media data

NASA Astrophysics Data System (ADS)

Pritzkau, Albert

2016-05-01

Social networks, in particular online social networks as a subset, enable the analysis of social relationships which are represented by interaction, collaboration, or other sorts of influence between people. Any set of people and their internal social relationships can be modelled as a general social graph. These relationships are formed by exchanging emails, making phone calls, or carrying out a range of other activities that build up the network. This paper presents an overview of current approaches to utilizing social media as a ubiquitous sensor network in the context of national and global security. Exploitation of social media is usually an interdisciplinary endeavour, in which the relevant technologies and methods are identified and linked in order ultimately demonstrate selected applications. Effective and efficient intelligence is usually accomplished in a combined human and computer effort. Indeed, the intelligence process heavily depends on combining a human's flexibility, creativity, and cognitive ability with the bandwidth and processing power of today's computers. To improve the usability and accuracy of the intelligence analysis we will have to rely on data-processing tools at the level of natural language. Especially the collection and transformation of unstructured data into actionable, structured data requires scalable computational algorithms ranging from Artificial Intelligence, via Machine Learning, to Natural Language Processing (NLP). To support intelligence analysis on social media data, social media analytics is concerned with developing and evaluating computational tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data. Analytics methods are employed to extract of significant patterns that might not be obvious. As a result, different data representations rendering distinct aspects of content and interactions serve as a means to adapt the focus of the intelligence analysis to specific information requests.

Sulfamerazine: Understanding the Influence of Slip Planes in the Polymorphic Phase Transformation through X-Ray Crystallographic Studies and ab Initio Lattice Dynamics.

PubMed

Pallipurath, Anuradha R; Skelton, Jonathan M; Warren, Mark R; Kamali, Naghmeh; McArdle, Patrick; Erxleben, Andrea

2015-10-05

Understanding the polymorphism exhibited by organic active-pharmaceutical ingredients (APIs), in particular the relationships between crystal structure and the thermodynamics of polymorph stability, is vital for the production of more stable drugs and better therapeutics, and for the economics of the pharmaceutical industry in general. In this article, we report a detailed study of the structure-property relationships among the polymorphs of the model API, Sulfamerazine. Detailed experimental characterization using synchrotron radiation is complemented by computational modeling of the lattice dynamics and mechanical properties, in order to study the origin of differences in millability and to investigate the thermodynamics of the phase equilibria. Good agreement is observed between the simulated phonon spectra and mid-infrared and Raman spectra. The presence of slip planes, which are found to give rise to low-frequency lattice vibrations, explains the higher millability of Form I compared to Form II. Energy/volume curves for the three polymorphs, together with the temperature dependence of the thermodynamic free energy computed from the phonon frequencies, explains why Form II converts to Form I at high temperature, whereas Form III is a rare polymorph that is difficult to isolate. The combined experimental and theoretical approach employed here should be generally applicable to the study of other systems that exhibit polymorphism.

Quantitative Structure--Activity Relationship Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Background: Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. Objective: In this study, a combinatorial QSAR approach has been employed for the creation of robust and predictive models of acute toxi...

STRUCTURE-ACTIVITY RELATIONSHIPS (SARS) AMONG MUTAGENS AND CARCINOGENS: A REVIEW

EPA Science Inventory

The review is an introduction to methods for evaluating structure-activity relationships (SARs), and, in particular, to those methods that have been applied to study mutagenicity and carcinogenicity. A brief history and some background material on the earliest attempts to correla...

QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS FOR CHEMICAL REDUCTIONS OF ORGANIC CONTAMINANTS

EPA Science Inventory

Sufficient kinetic data on abiotic reduction reactions involving organic contaminants are now available that quantitative structure-activity relationships (QSARs) for these reactions can be developed. Over 50 QSARs have been reported, most in just the last few years, and they ar...

Computational Structures Technology for Airframes and Propulsion Systems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler); Housner, Jerrold M. (Compiler); Starnes, James H., Jr. (Compiler); Hopkins, Dale A. (Compiler); Chamis, Christos C. (Compiler)

1992-01-01

This conference publication contains the presentations and discussions from the joint University of Virginia (UVA)/NASA Workshops. The presentations included NASA Headquarters perspectives on High Speed Civil Transport (HSCT), goals and objectives of the UVA Center for Computational Structures Technology (CST), NASA and Air Force CST activities, CST activities for airframes and propulsion systems in industry, and CST activities at Sandia National Laboratory.

Characterizing Interaction with Visual Mathematical Representations

ERIC Educational Resources Information Center

Sedig, Kamran; Sumner, Mark

2006-01-01

This paper presents a characterization of computer-based interactions by which learners can explore and investigate visual mathematical representations (VMRs). VMRs (e.g., geometric structures, graphs, and diagrams) refer to graphical representations that visually encode properties and relationships of mathematical structures and concepts.…

Structural Characteristics and Reactivity Relationships of Nitroaromatic and Nitramine Explosives – A Review of Our Computational Chemistry and Spectroscopic Research

PubMed Central

Qasim, Mohammad M.; Moore, Brett; Taylor, Lyssa; Honea, Patricia; Gorb, Leonid; Leszczynski, Jerzy

2007-01-01

Although much has been discovered, discussed and written as to problems of contamination by various military unique compounds, particularly by the nitrogen based energetics (NOCs), remaining problems dictate further evaluation of actual and potential risk to the environment by these energetics and their derivatives and metabolites through determination of their environmental impact—transport, fate and toxicity. This work comprises an effort to understand structural relationships and degradation mechanisms of current and emerging explosives, including nitroaromatic; cyclic and cage cyclic nitramine; and a nitrocubane. This review of our computational chemistry and spectroscopic research describes and compares competitive degradation mechanisms by free radical oxidative, reductive and alkali hydrolysis, relating them, when possible, to environmental risk.

Task allocation model for minimization of completion time in distributed computer systems

NASA Astrophysics Data System (ADS)

Wang, Jai-Ping; Steidley, Carl W.

1993-08-01

A task in a distributed computing system consists of a set of related modules. Each of the modules will execute on one of the processors of the system and communicate with some other modules. In addition, precedence relationships may exist among the modules. Task allocation is an essential activity in distributed-software design. This activity is of importance to all phases of the development of a distributed system. This paper establishes task completion-time models and task allocation models for minimizing task completion time. Current work in this area is either at the experimental level or without the consideration of precedence relationships among modules. The development of mathematical models for the computation of task completion time and task allocation will benefit many real-time computer applications such as radar systems, navigation systems, industrial process control systems, image processing systems, and artificial intelligence oriented systems.

Computational Insight into Protein Tyrosine Phosphatase 1B Inhibition: A Case Study of the Combined Ligand- and Structure-Based Approach.

PubMed

Zhang, Xiangyu; Jiang, Hailun; Li, Wei; Wang, Jian; Cheng, Maosheng

2017-01-01

Protein tyrosine phosphatase 1B (PTP1B) is an attractive target for treating cancer, obesity, and type 2 diabetes. In our work, the way of combined ligand- and structure-based approach was applied to analyze the characteristics of PTP1B enzyme and its interaction with competitive inhibitors. Firstly, the pharmacophore model of PTP1B inhibitors was built based on the common feature of sixteen compounds. It was found that the pharmacophore model consisted of five chemical features: one aromatic ring (R) region, two hydrophobic (H) groups, and two hydrogen bond acceptors (A). To further elucidate the binding modes of these inhibitors with PTP1B active sites, four docking programs (AutoDock 4.0, AutoDock Vina 1.0, standard precision (SP) Glide 9.7, and extra precision (XP) Glide 9.7) were used. The characteristics of the active sites were then described by the conformations of the docking results. In conclusion, a combination of various pharmacophore features and the integration information of structure activity relationship (SAR) can be used to design novel potent PTP1B inhibitors.

Characterization of SNPs in the dopamine-β-hydroxylase gene providing new insights into its structure-function relationship.

PubMed

Punchaichira, Toyanji Joseph; Dey, Sanjay Kumar; Mukhopadhyay, Anirban; Kundu, Suman; Thelma, B K

2017-07-01

Dopamine-β-hydroxylase (DBH, EC 1.14.17.1), an oxido-reductase that catalyses the conversion of dopamine to norepinephrine, is largely expressed in sympathetic neurons and adrenal medulla. Several regulatory and structural variants in DBH associated with various neuropsychiatric, cardiovascular diseases and a few that may determine enzyme activity have also been identified. Due to paucity of studies on functional characterization of DBH variants, its structure-function relationship is poorly understood. The purpose of the study was to characterize five non-synonymous (ns) variants that were prioritized either based on previous association studies or Sorting Tolerant From Intolerant (SIFT) algorithm. The DBH ORF with wild type (WT) and site-directed mutagenized variants were transfected into HEK293 cells to generate transient and stable lines expressing these variant enzymes. Activity was determined by UPLC-PDA and corresponding quantity by MRM HR on a TripleTOF 5600 MS respectively of spent media from stable cell lines. Homospecific activity computed for the WT and variant proteins showed a marginal decrease in A318S, W544S and R549C variants. In transient cell lines, differential secretion was observed in the case of L317P, W544S and R549C. Secretory defect in L317P was confirmed by localization in ER. R549C exhibited both decreased homospecific activity and differential secretion. Of note, all the variants were seen to be destabilizing based on in silico folding analysis and molecular dynamics (MD) simulation, lending support to our experimental observations. These novel genotype-phenotype correlations in this gene of considerable pharmacological relevance have implications for dopamine-related disorders.

Systematic size study of an insect antifreeze protein and its interaction with ice.

PubMed

Liu, Kai; Jia, Zongchao; Chen, Guangju; Tung, Chenho; Liu, Ruozhuang

2005-02-01

Because of their remarkable ability to depress the freezing point of aqueous solutions, antifreeze proteins (AFPs) play a critical role in helping many organisms survive subzero temperatures. The beta-helical insect AFP structures solved to date, consisting of multiple repeating circular loops or coils, are perhaps the most regular protein structures discovered thus far. Taking an exceptional advantage of the unusually high structural regularity of insect AFPs, we have employed both semiempirical and quantum mechanics computational approaches to systematically investigate the relationship between the number of AFP coils and the AFP-ice interaction energy, an indicator of antifreeze activity. We generated a series of AFP models with varying numbers of 12-residue coils (sequence TCTxSxxCxxAx) and calculated their interaction energies with ice. Using several independent computational methods, we found that the AFP-ice interaction energy increased as the number of coils increased, until an upper bound was reached. The increase of interaction energy was significant for each of the first five coils, and there was a clear synergism that gradually diminished and even decreased with further increase of the number of coils. Our results are in excellent agreement with the recently reported experimental observations.

Systematic Size Study of an Insect Antifreeze Protein and Its Interaction with Ice

PubMed Central

Liu, Kai; Jia, Zongchao; Chen, Guangju; Tung, Chenho; Liu, Ruozhuang

2005-01-01

Because of their remarkable ability to depress the freezing point of aqueous solutions, antifreeze proteins (AFPs) play a critical role in helping many organisms survive subzero temperatures. The β-helical insect AFP structures solved to date, consisting of multiple repeating circular loops or coils, are perhaps the most regular protein structures discovered thus far. Taking an exceptional advantage of the unusually high structural regularity of insect AFPs, we have employed both semiempirical and quantum mechanics computational approaches to systematically investigate the relationship between the number of AFP coils and the AFP-ice interaction energy, an indicator of antifreeze activity. We generated a series of AFP models with varying numbers of 12-residue coils (sequence TCTxSxxCxxAx) and calculated their interaction energies with ice. Using several independent computational methods, we found that the AFP-ice interaction energy increased as the number of coils increased, until an upper bound was reached. The increase of interaction energy was significant for each of the first five coils, and there was a clear synergism that gradually diminished and even decreased with further increase of the number of coils. Our results are in excellent agreement with the recently reported experimental observations. PMID:15713600

Computational design of molecules for an all-quinone redox flow battery.

PubMed

Er, Süleyman; Suh, Changwon; Marshak, Michael P; Aspuru-Guzik, Alán

2015-02-01

Inspired by the electron transfer properties of quinones in biological systems, we recently showed that quinones are also very promising electroactive materials for stationary energy storage applications. Due to the practically infinite chemical space of organic molecules, the discovery of additional quinones or other redox-active organic molecules for energy storage applications is an open field of inquiry. Here, we introduce a high-throughput computational screening approach that we applied to an accelerated study of a total of 1710 quinone (Q) and hydroquinone (QH 2 ) ( i.e. , two-electron two-proton) redox couples. We identified the promising candidates for both the negative and positive sides of organic-based aqueous flow batteries, thus enabling an all-quinone battery. To further aid the development of additional interesting electroactive small molecules we also provide emerging quantitative structure-property relationships.

Structure-based discovery of fiber-binding compounds that reduce the cytotoxicity of amyloid beta

DOE PAGES

Jiang, Lin; Liu, Cong; Leibly, David; ...

2013-07-16

Amyloid protein aggregates are associated with dozens of devastating diseases including Alzheimer’s, Parkinson’s, ALS, and diabetes type 2. While structure-based discovery of compounds has been effective in combating numerous infectious and metabolic diseases, ignorance of amyloid structure has hindered similar approaches to amyloid disease. Here we show that knowledge of the atomic structure of one of the adhesive, steric-zipper segments of the amyloid-beta (Aβ) protein of Alzheimer’s disease, when coupled with computational methods, identifies eight diverse but mainly flat compounds and three compound derivatives that reduce Aβ cytotoxicity against mammalian cells by up to 90%. Although these compounds bind tomore » Aβ fibers, they do not reduce fiber formation of Aβ. Structure-activity relationship studies of the fiber-binding compounds and their derivatives suggest that compound binding increases fiber stability and decreases fiber toxicity, perhaps by shifting the equilibrium of Aβ from oligomers to fibers.« less

Effect of Material Ion Exchanges on the Mechanical Stiffness Properties and Shear Deformation of Hydrated Cement Material Chemistry Structure C-S-H Jennit - A Computational Modeling Study

DTIC Science & Technology

2014-01-01

Study Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to...understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus...find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance are required. A computational material

Teachers' Organization of Participation Structures for Teaching Science with Computer Technology

ERIC Educational Resources Information Center

Subramaniam, Karthigeyan

2016-01-01

This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and…

Structural Relationships between Social Activities and Longitudinal Trajectories of Depression among Older Adults

ERIC Educational Resources Information Center

Hong, Song-Iee; Hasche, Leslie; Bowland, Sharon

2009-01-01

Purpose: This study examines the structural relationships between social activities and trajectories of late-life depression. Design and Methods: Latent class analysis was used with a nationally representative sample of older adults (N = 5,294) from the Longitudinal Study on Aging II to classify patterns of social activities. A latent growth curve…

Transformation products in the water cycle and the unsolved problem of their proactive assessment: A combined in vitro/in silico approach.

PubMed

Menz, Jakob; Toolaram, Anju Priya; Rastogi, Tushar; Leder, Christoph; Olsson, Oliver; Kümmerer, Klaus; Schneider, Mandy

2017-01-01

Transformation products (TPs) emerging from incomplete degradation of micropollutants in aquatic systems can retain the biological activity of the parent compound, or may even possess new unexpected toxic properties. The chemical identities of these substances remain largely unknown, and consequently, the risks caused by their presence in the water cycle cannot be assessed thoroughly. In this study, a combined approach for the proactive identification of hazardous elements in the chemical structures of TPs, comprising analytical, bioanalytical and computational methods, was assessed by the example of the pharmaceutically active micropollutant propranolol (PPL). PPL was photo-transformed using ultraviolet (UV) irradiation and 115 newly formed TPs were monitored in the reaction mixtures by LC-MS analysis. The reaction mixtures were screened for emerging effects using a battery of in vitro bioassays and the occurrence of cytotoxic and mutagenic activities in bacteria was found to be significantly correlated with the occurrence of specific TPs during the treatment process. The follow-up analysis of structure-activity-relationships further illustrated that only small chemical transformations, such as the hydroxylation or the oxidative opening of an aromatic ring system, could substantially alter the biological effects of micropollutants in aquatic systems. In conclusion, more efforts should be made to prevent the occurrence and transformation of micropollutants in the water cycle and to identify the principal degradation pathways leading to their toxicological activation. With regard to the latter, the judicious combination of bioanalytical and computational tools represents an appealing approach that should be developed further. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.

Computer work and self-reported variables on anthropometrics, computer usage, work ability, productivity, pain, and physical activity.

PubMed

Madeleine, Pascal; Vangsgaard, Steffen; Hviid Andersen, Johan; Ge, Hong-You; Arendt-Nielsen, Lars

2013-08-01

Computer users often report musculoskeletal complaints and pain in the upper extremities and the neck-shoulder region. However, recent epidemiological studies do not report a relationship between the extent of computer use and work-related musculoskeletal disorders (WMSD).The aim of this study was to conduct an explorative analysis on short and long-term pain complaints and work-related variables in a cohort of Danish computer users. A structured web-based questionnaire including questions related to musculoskeletal pain, anthropometrics, work-related variables, work ability, productivity, health-related parameters, lifestyle variables as well as physical activity during leisure time was designed. Six hundred and ninety office workers completed the questionnaire responding to an announcement posted in a union magazine. The questionnaire outcomes, i.e., pain intensity, duration and locations as well as anthropometrics, work-related variables, work ability, productivity, and level of physical activity, were stratified by gender and correlations were obtained. Women reported higher pain intensity, longer pain duration as well as more locations with pain than men (P < 0.05). In parallel, women scored poorer work ability and ability to fulfil the requirements on productivity than men (P < 0.05). Strong positive correlations were found between pain intensity and pain duration for the forearm, elbow, neck and shoulder (P < 0.001). Moderate negative correlations were seen between pain intensity and work ability/productivity (P < 0.001). The present results provide new key information on pain characteristics in office workers. The differences in pain characteristics, i.e., higher intensity, longer duration and more pain locations as well as poorer work ability reported by women workers relate to their higher risk of contracting WMSD. Overall, this investigation confirmed the complex interplay between anthropometrics, work ability, productivity, and pain perception among computer users.

Computational design of molecules for an all-quinone redox flow battery† †Electronic supplementary information (ESI) available: The list of computationally predicted candidate quinone molecules with interesting redox properties. See DOI: 10.1039/c4sc03030c Click here for additional data file.

PubMed Central

Er, Süleyman; Suh, Changwon; Marshak, Michael P.

2015-01-01

Inspired by the electron transfer properties of quinones in biological systems, we recently showed that quinones are also very promising electroactive materials for stationary energy storage applications. Due to the practically infinite chemical space of organic molecules, the discovery of additional quinones or other redox-active organic molecules for energy storage applications is an open field of inquiry. Here, we introduce a high-throughput computational screening approach that we applied to an accelerated study of a total of 1710 quinone (Q) and hydroquinone (QH2) (i.e., two-electron two-proton) redox couples. We identified the promising candidates for both the negative and positive sides of organic-based aqueous flow batteries, thus enabling an all-quinone battery. To further aid the development of additional interesting electroactive small molecules we also provide emerging quantitative structure-property relationships. PMID:29560173

Spatio-Temporal Story Mapping Animation Based On Structured Causal Relationships Of Historical Events

NASA Astrophysics Data System (ADS)

Inoue, Y.; Tsuruoka, K.; Arikawa, M.

2014-04-01

In this paper, we proposed a user interface that displays visual animations on geographic maps and timelines for depicting historical stories by representing causal relationships among events for time series. We have been developing an experimental software system for the spatial-temporal visualization of historical stories for tablet computers. Our proposed system makes people effectively learn historical stories using visual animations based on hierarchical structures of different scale timelines and maps.

Recent developments in structural proteomics for protein structure determination.

PubMed

Liu, Hsuan-Liang; Hsu, Jyh-Ping

2005-05-01

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

Hidden relationships between metalloproteins unveiled by structural comparison of their metal sites

NASA Astrophysics Data System (ADS)

Valasatava, Yana; Andreini, Claudia; Rosato, Antonio

2015-03-01

Metalloproteins account for a substantial fraction of all proteins. They incorporate metal atoms, which are required for their structure and/or function. Here we describe a new computational protocol to systematically compare and classify metal-binding sites on the basis of their structural similarity. These sites are extracted from the MetalPDB database of minimal functional sites (MFSs) in metal-binding biological macromolecules. Structural similarity is measured by the scoring function of the available MetalS2 program. Hierarchical clustering was used to organize MFSs into clusters, for each of which a representative MFS was identified. The comparison of all representative MFSs provided a thorough structure-based classification of the sites analyzed. As examples, the application of the proposed computational protocol to all heme-binding proteins and zinc-binding proteins of known structure highlighted the existence of structural subtypes, validated known evolutionary links and shed new light on the occurrence of similar sites in systems at different evolutionary distances. The present approach thus makes available an innovative viewpoint on metalloproteins, where the functionally crucial metal sites effectively lead the discovery of structural and functional relationships in a largely protein-independent manner.

The importance of employing computational resources for the automation of drug discovery.

PubMed

Rosales-Hernández, Martha Cecilia; Correa-Basurto, José

2015-03-01

The application of computational tools to drug discovery helps researchers to design and evaluate new drugs swiftly with a reduce economic resources. To discover new potential drugs, computational chemistry incorporates automatization for obtaining biological data such as adsorption, distribution, metabolism, excretion and toxicity (ADMET), as well as drug mechanisms of action. This editorial looks at examples of these computational tools, including docking, molecular dynamics simulation, virtual screening, quantum chemistry, quantitative structural activity relationship, principal component analysis and drug screening workflow systems. The authors then provide their perspectives on the importance of these techniques for drug discovery. Computational tools help researchers to design and discover new drugs for the treatment of several human diseases without side effects, thus allowing for the evaluation of millions of compounds with a reduced cost in both time and economic resources. The problem is that operating each program is difficult; one is required to use several programs and understand each of the properties being tested. In the future, it is possible that a single computer and software program will be capable of evaluating the complete properties (mechanisms of action and ADMET properties) of ligands. It is also possible that after submitting one target, this computer-software will be capable of suggesting potential compounds along with ways to synthesize them, and presenting biological models for testing.

Moderators, mediators, and bidirectional relationships in the International Classification of Functioning, Disability and Health (ICF) framework: An empirical investigation using a longitudinal design and Structural Equation Modeling (SEM).

PubMed

Rouquette, Alexandra; Badley, Elizabeth M; Falissard, Bruno; Dub, Timothée; Leplege, Alain; Coste, Joël

2015-06-01

The International Classification of Functioning, Disability and Health (ICF) published in 2001 describes the consequences of health conditions with three components of impairments in body structures or functions, activity limitations and participation restrictions. Two of the new features of the conceptual model were the possibility of feedback effects between each ICF component and the introduction of contextual factors conceptualized as moderators of the relationship between the components. The aim of this longitudinal study is to provide empirical evidence of these two kinds of effect. Structural equation modeling was used to analyze data from a French population-based cohort of 548 patients with knee osteoarthritis recruited between April 2007 and March 2009 and followed for three years. Indicators of the body structure and function, activity and participation components of the ICF were derived from self-administered standardized instruments. The measurement model revealed four separate factors for body structures impairments, body functions impairments, activity limitations and participation restrictions. The classic sequence from body impairments to participation restrictions through activity limitations was found at each assessment time. Longitudinal study of the ICF component relationships showed a feedback pathway indicating that the level of participation restrictions at baseline was predictive of activity limitations three years later. Finally, the moderating role of personal (age, sex, mental health, etc.) and environmental factors (family relationships, mobility device use, etc.) was investigated. Three contextual factors (sex, family relationships and walking stick use) were found to be moderators for the relationship between the body impairments and the activity limitations components. Mental health was found to be a mediating factor of the effect of activity limitations on participation restrictions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Seismic design of passive tuned mass damper parameters using active control algorithm

NASA Astrophysics Data System (ADS)

Chang, Chia-Ming; Shia, Syuan; Lai, Yong-An

2018-07-01

Tuned mass dampers are a widely-accepted control method to effectively reduce the vibrations of tall buildings. A tuned mass damper employs a damped harmonic oscillator with specific dynamic characteristics, thus the response of structures can be regulated by the additive dynamics. The additive dynamics are, however, similar to the feedback control system in active control. Therefore, the objective of this study is to develop a new tuned mass damper design procedure based on the active control algorithm, i.e., the H2/LQG control. This design facilitates the similarity of feedback control in the active control algorithm to determine the spring and damper in a tuned mass damper. Given a mass ratio between the damper and structure, the stiffness and damping coefficient of the tuned mass damper are derived by minimizing the response objective function of the primary structure, where the structural properties are known. Varying a single weighting in this objective function yields the optimal TMD design when the minimum peak in the displacement transfer function of the structure with the TMD is met. This study examines various objective functions as well as derives the associated equations to compute the stiffness and damping coefficient. The relationship between the primary structure and optimal tuned mass damper is parametrically studied. Performance is evaluated by exploring the h2-and h∞-norms of displacements and accelerations of the primary structure. In time-domain analysis, the damping effectiveness of the tune mass damper controlled structures is investigated under impulse excitation. Structures with the optimal tuned mass dampers are also assessed under seismic excitation. As a result, the proposed design procedure produces an effective tuned mass damper to be employed in a structure against earthquakes.

Teachers' Organization of Participation Structures for Teaching Science with Computer Technology

NASA Astrophysics Data System (ADS)

Subramaniam, Karthigeyan

2016-08-01

This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and processes in social settings like classrooms thereby providing glimpses into the complex dynamics of teacher-students interactions, configurations, and conventions during collective meaning making and knowledge creation. Data included observations, interviews, and focus group interviews. Analysis revealed that the dominant participation structure evident within participants' instruction with computer technology was ( Teacher) initiation-( Student and Teacher) response sequences-( Teacher) evaluate participation structure. Three key events characterized the how participants organized this participation structure in their classrooms: setting the stage for interactive instruction, the joint activity, and maintaining accountability. Implications include the following: (1) teacher educators need to tap into the knowledge base that underscores science teachers' learning to teach philosophies when computer technology is used in instruction. (2) Teacher educators need to emphasize the essential idea that learning and cognition is not situated within the computer technology but within the pedagogical practices, specifically the participation structures. (3) The pedagogical practices developed with the integration or with the use of computer technology underscored by the teachers' own knowledge of classroom contexts and curriculum needs to be the focus for how students learn science content with computer technology instead of just focusing on how computer technology solely supports students learning of science content.

Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure - Activity Relationships (PCSAR).

PubMed

Kamath, Padmaja; Fernandez, Alberto; Giralt, Francesc; Rallo, Robert

2015-01-01

Nanoparticles are likely to interact in real-case application scenarios with mixtures of proteins and biomolecules that will absorb onto their surface forming the so-called protein corona. Information related to the composition of the protein corona and net cell association was collected from literature for a library of surface-modified gold and silver nanoparticles. For each protein in the corona, sequence information was extracted and used to calculate physicochemical properties and statistical descriptors. Data cleaning and preprocessing techniques including statistical analysis and feature selection methods were applied to remove highly correlated, redundant and non-significant features. A weighting technique was applied to construct specific signatures that represent the corona composition for each nanoparticle. Using this basic set of protein descriptors, a new Protein Corona Structure-Activity Relationship (PCSAR) that relates net cell association with the physicochemical descriptors of the proteins that form the corona was developed and validated. The features that resulted from the feature selection were in line with already published literature, and the computational model constructed on these features had a good accuracy (R(2)LOO=0.76 and R(2)LMO(25%)=0.72) and stability, with the advantage that the fingerprints based on physicochemical descriptors were independent of the specific proteins that form the corona.

Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship.

PubMed

Luo, Wen; Medrek, Sarah; Misra, Jatin; Nohynek, Gerhard J

2007-02-01

The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K(ow) values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K(p) (R2 = 0.8225): logK(ow), X0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations.

Artificial intelligence approaches for rational drug design and discovery.

PubMed

Duch, Włodzisław; Swaminathan, Karthikeyan; Meller, Jarosław

2007-01-01

Pattern recognition, machine learning and artificial intelligence approaches play an increasingly important role in rational drug design, screening and identification of candidate molecules and studies on quantitative structure-activity relationships (QSAR). In this review, we present an overview of basic concepts and methodology in the fields of machine learning and artificial intelligence (AI). An emphasis is put on methods that enable an intuitive interpretation of the results and facilitate gaining an insight into the structure of the problem at hand. We also discuss representative applications of AI methods to docking, screening and QSAR studies. The growing trend to integrate computational and experimental efforts in that regard and some future developments are discussed. In addition, we comment on a broader role of machine learning and artificial intelligence approaches in biomedical research.

Simulation of an array-based neural net model

NASA Technical Reports Server (NTRS)

Barnden, John A.

1987-01-01

Research in cognitive science suggests that much of cognition involves the rapid manipulation of complex data structures. However, it is very unclear how this could be realized in neural networks or connectionist systems. A core question is: how could the interconnectivity of items in an abstract-level data structure be neurally encoded? The answer appeals mainly to positional relationships between activity patterns within neural arrays, rather than directly to neural connections in the traditional way. The new method was initially devised to account for abstract symbolic data structures, but it also supports cognitively useful spatial analogue, image-like representations. As the neural model is based on massive, uniform, parallel computations over 2D arrays, the massively parallel processor is a convenient tool for simulation work, although there are complications in using the machine to the fullest advantage. An MPP Pascal simulation program for a small pilot version of the model is running.

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

PubMed Central

Cronin, Mark T.D.; Enoch, Steven J.; Mellor, Claire L.; Przybylak, Katarzyna R.; Richarz, Andrea-Nicole; Madden, Judith C.

2017-01-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given. PMID:28744348

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.

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects.

PubMed

Cronin, Mark T D; Enoch, Steven J; Mellor, Claire L; Przybylak, Katarzyna R; Richarz, Andrea-Nicole; Madden, Judith C

2017-07-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

Developing Higher-Order Materials Knowledge Systems

NASA Astrophysics Data System (ADS)

Fast, Anthony Nathan

2011-12-01

Advances in computational materials science and novel characterization techniques have allowed scientists to probe deeply into a diverse range of materials phenomena. These activities are producing enormous amounts of information regarding the roles of various hierarchical material features in the overall performance characteristics displayed by the material. Connecting the hierarchical information over disparate domains is at the crux of multiscale modeling. The inherent challenge of performing multiscale simulations is developing scale bridging relationships to couple material information between well separated length scales. Much progress has been made in the development of homogenization relationships which replace heterogeneous material features with effective homogenous descriptions. These relationships facilitate the flow of information from lower length scales to higher length scales. Meanwhile, most localization relationships that link the information from a from a higher length scale to a lower length scale are plagued by computationally intensive techniques which are not readily integrated into multiscale simulations. The challenge of executing fully coupled multiscale simulations is augmented by the need to incorporate the evolution of the material structure that may occur under conditions such as material processing. To address these challenges with multiscale simulation, a novel framework called the Materials Knowledge System (MKS) has been developed. This methodology efficiently extracts, stores, and recalls microstructure-property-processing localization relationships. This approach is built on the statistical continuum theories developed by Kroner that express the localization of the response field at the microscale using a series of highly complex convolution integrals, which have historically been evaluated analytically. The MKS approach dramatically improves the accuracy of these expressions by calibrating the convolution kernels in these expressions to results from previously validated physics-based models. These novel tools have been validated for the elastic strain localization in moderate contrast dual-phase composites by direct comparisons with predictions from finite element model. The versatility of the approach is further demonstrated by its successful application to capturing the structure evolution during spinodal decomposition of a binary alloy. Lastly, some key features in the future application of the MKS approach are developed using the Portevin-le Chaterlier effect. It has been shown with these case studies that the MKS approach is capable of accurately reproducing the results from physics based models with a drastic reduction in computational requirements.

Relationship between Computer-Based Reading Activities and Reading Achievements among Hong Kong and U.S. Students: A Comparative Study Using PIRLS 2011 Data

ERIC Educational Resources Information Center

Li, Dan; Wang, Jian

2014-01-01

Reading for personal interest and acquiring and using information using various reading processes are important parts of reading literacy that students need to develop in order to progress successfully through their schooling and fully function in the information society. Computer assisted reading instructional activities are assumed useful in…

X-ray structures of the anticoagulants coumatetralyl and chlorophacinone. Theoretical calculations and SAR investigations on thirteen anticoagulant rodenticides

NASA Astrophysics Data System (ADS)

Dolmella, A.; Gatto, S.; Girardi, E.; Bandoli, G.

1999-12-01

Coumatetralyl and chlorophacinone, two substances related to 4-hydroxycoumarin (HC) and to 1,3-indandione (ID), respectively, show activity as anticoagulant rodenticides. In the present study we have investigated the solid-state structures of coumatetralyl and chlorophacinone by means of X-ray single-crystal and powder diffraction, along with thermal analysis. The crystal structures of the two compounds have been used as input geometries for a series of computational chemistry efforts, involving other anticoagulant derivatives as well. Thus, ab initio, semiempirical molecular orbital, molecular mechanics and molecular dynamics/simulated annealing calculations have been performed on thirteen anticoagulant rodenticides. In particular, the annealing calculations have been made to assess the conformational freedom of the compounds under scrutiny. All the generated conformers have been classified into families. The classification has first been made empirically, and then validated by means of a cluster analysis. A number of structural and physico-chemical parameters derived from the calculations has been used in turn for structure-activity relationships (SARs) investigations. In the latter, we have assessed how the selected parameters affect toxicity. The results seem to be consistent with a three-dimensional biophore model, in which higher toxicity is predicted for the more voluminous rodenticides. We suggest that these compounds better fit the active site of the target enzyme vitamin K 2,3-epoxide reductase (KO-reductase).

Molecular Modeling on Berberine Derivatives toward BuChE: An Integrated Study with Quantitative Structure-Activity Relationships Models, Molecular Docking, and Molecular Dynamics Simulations.

PubMed

Fang, Jiansong; Pang, Xiaocong; Wu, Ping; Yan, Rong; Gao, Li; Li, Chao; Lian, Wenwen; Wang, Qi; Liu, Ai-lin; Du, Guan-hua

2016-05-01

A dataset of 67 berberine derivatives for the inhibition of butyrylcholinesterase (BuChE) was studied based on the combination of quantitative structure-activity relationships models, molecular docking, and molecular dynamics methods. First, a series of berberine derivatives were reported, and their inhibitory activities toward butyrylcholinesterase (BuChE) were evaluated. By 2D- quantitative structure-activity relationships studies, the best model built by partial least-square had a conventional correlation coefficient of the training set (R(2)) of 0.883, a cross-validation correlation coefficient (Qcv2) of 0.777, and a conventional correlation coefficient of the test set (Rpred2) of 0.775. The model was also confirmed by Y-randomization examination. In addition, the molecular docking and molecular dynamics simulation were performed to better elucidate the inhibitory mechanism of three typical berberine derivatives (berberine, C2, and C55) toward BuChE. The predicted binding free energy results were consistent with the experimental data and showed that the van der Waals energy term (ΔEvdw) difference played the most important role in differentiating the activity among the three inhibitors (berberine, C2, and C55). The developed quantitative structure-activity relationships models provide details on the fine relationship linking structure and activity and offer clues for structural modifications, and the molecular simulation helps to understand the inhibitory mechanism of the three typical inhibitors. In conclusion, the results of this study provide useful clues for new drug design and discovery of BuChE inhibitors from berberine derivatives. © 2015 John Wiley & Sons A/S.

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Automated Program Recognition by Graph Parsing

DTIC Science & Technology

1992-07-01

structures (cliches) in a program can help an experienced programmer understand the program. Based on the known relationships between the clichis, a...Graph Parsing Linda Mary Wills Abstract The recognition of standard computational structures (cliches) in a program can help an experienced programmer...3.4.1 Structure -Sharing ....... ............................ 76 3.4.2 Aggregation ....................................... 80 2 3.5 Chart Parsing Flow

Phyto-fungicides: Structure activity relationships of the thymol derivatives against Rhizoctonia solani

USDA-ARS?s Scientific Manuscript database

Thymol, the key component of thyme oil and its derivatives were evaluated for their structure activity relationship as fungicide against Rhizoctonia solani. Since plant based chemicals are considered as “Generally Recognized as Safe” (GRAS) chemicals, there is a great potential to use phytochemicals...

ESTIMATION OF MICROBIAL REDUCTIVE TRANSFORMATION RATES FOR CHLORINATED BENZENES AND PHENOLS USING A QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP APPROACH

EPA Science Inventory

A set of literature data was used to derive several quantitative structure-activity relationships (QSARs) to predict the rate constants for the microbial reductive dehalogenation of chlorinated aromatics. Dechlorination rate constants for 25 chloroaromatics were corrected for th...

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models

EPA Science Inventory

The present study explores the merit of utilizing available pharmaceutical data to construct a quantitative structure-activity relationship (QSAR) for prediction of the fraction of a chemical unbound to plasma protein (Fub) in environmentally relevant compounds. Independent model...

Sequence-Dependent Structure/Function Relationships of Catalytic Peptide-Enabled Gold Nanoparticles Generated under Ambient Synthetic Conditions

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

Bedford, Nicholas M.; Hughes, Zak E.; Tang, Zhenghua

Peptide-enabled nanoparticle (NP) synthesis routes can create and/or assemble functional nanomaterials under environmentally friendly conditions, with properties dictated by complex interactions at the biotic/abiotic interface. Manipulation of this interface through sequence modification can provide the capability for material properties to be tailored to create enhanced materials for energy, catalysis, and sensing applications. Fully realizing the potential of these materials requires a comprehensive understanding of sequence-dependent structure/function relationships that is presently lacking. In this work, the atomic-scale structures of a series of peptide-capped Au NPs are determined using a combination of atomic pair distribution function analysis of high-energy X-ray diffraction datamore » and advanced molecular dynamics (MD) simulations. The Au NPs produced with different peptide sequences exhibit varying degrees of catalytic activity for the exemplar reaction 4-nitrophenol reduction. The experimentally derived atomic-scale NP configurations reveal sequence-dependent differences in structural order at the NP surface. Replica exchange with solute-tempering MD simulations are then used to predict the morphology of the peptide overlayer on these Au NPs and identify factors determining the structure/catalytic properties relationship. We show that the amount of exposed Au surface, the underlying surface structural disorder, and the interaction strength of the peptide with the Au surface all influence catalytic performance. A simplified computational prediction of catalytic performance is developed that can potentially serve as a screening tool for future studies. Our approach provides a platform for broadening the analysis of catalytic peptide-enabled metallic NP systems, potentially allowing for the development of rational design rules for property enhancement.« less

CSM parallel structural methods research

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1989-01-01

Parallel structural methods, research team activities, advanced architecture computers for parallel computational structural mechanics (CSM) research, the FLEX/32 multicomputer, a parallel structural analyses testbed, blade-stiffened aluminum panel with a circular cutout and the dynamic characteristics of a 60 meter, 54-bay, 3-longeron deployable truss beam are among the topics discussed.

Conformational changes of an ion-channel during gating and emerging electrophysiologic properties: Application of a computational approach to cardiac Kv7.1.

PubMed

Nekouzadeh, Ali; Rudy, Yoram

2016-01-01

Ion channels are the "building blocks" of the excitation process in excitable tissues. Despite advances in determining their molecular structure, understanding the relationship between channel protein structure and electrical excitation remains a challenge. The Kv7.1 potassium channel is an important determinant of the cardiac action potential and its adaptation to rate changes. It is subject to beta adrenergic regulation, and many mutations in the channel protein are associated with the arrhythmic long QT syndrome. In this theoretical study, we use a novel computational approach to simulate the conformational changes that Kv7.1 undergoes during activation gating and compute the resulting electrophysiologic function in terms of single-channel and macroscopic currents. We generated all possible conformations of the S4-S5 linker that couples the S3-S4 complex (voltage sensor domain, VSD) to the pore, and all associated conformations of VSD and the pore (S6). Analysis of these conformations revealed that VSD-to-pore mechanical coupling during activation gating involves outward translation of the voltage sensor, accompanied by a translation away from the pore and clockwise twist. These motions cause pore opening by moving the S4-S5 linker upward and away from the pore, providing space for the S6 tails to move away from each other. Single channel records, computed from the simulated motion trajectories during gating, have stochastic properties similar to experimentally recorded traces. Macroscopic current through an ensemble of channels displays two key properties of Kv7.1: an initial delay of activation and fast inactivation. The simulations suggest a molecular mechanism for fast inactivation; a large twist of the VSD following its outward translation results in movement of the base of the S4-S5 linker toward the pore, eliminating open pore conformations to cause inactivation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Adult-Supplied Structure and Children's Activity Levels.

ERIC Educational Resources Information Center

Carpenter, C. J.; And Others

This study investigated the relationship between preschool children's participation in play activities structured by adults and the level of motor activity children exhibited while in those activities, to test the hypothesis that children's motor activity levels vary according to the level of structure imposed on activities by adults. Subjects…

Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization

PubMed Central

2012-01-01

Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection. PMID:23046104

Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

Neural networks and inductive logic programming (ILP) have been compared to linear regression for modelling the QSAR of the inhibition of E. coli dihydrofolate reductase (DHFR) by 2,4-diamino-5-(substitured benzyl)pyrimidines, and, in the subsequent paper [Hirst, J.D., King, R.D. and Sternberg, M.J.E., J. Comput.-Aided Mol. Design, 8 (1994) 421], the inhibition of rodent DHFR by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazines. Cross-validation trials provide a statistically rigorous assessment of the predictive capabilities of the methods, with training and testing data selected randomly and all the methods developed using identical training data. For the ILP analysis, molecules are represented by attributes other than Hansch parameters. Neural networks and ILP perform better than linear regression using the attribute representation, but the difference is not statistically significant. The major benefit from the ILP analysis is the formulation of understandable rules relating the activity of the inhibitors to their chemical structure.

Structural analysis of natural textures.

PubMed

Vilnrotter, F M; Nevatia, R; Price, K E

1986-01-01

Many textures can be described structurally, in terms of the individual textural elements and their spatial relationships. This paper describes a system to generate useful descriptions of natural textures in these terms. The basic approach is to determine an initial, partial description of the elements using edge features. This description controls the extraction of the texture elements. The elements are grouped by type, and spatial relationships between elements are computed. The descriptions are shown to be useful for recognition of the textures, and for reconstruction of periodic textures.

Structure-Property Relationships for Tailoring Phenoxazines as Reducing Photoredox Catalysts.

PubMed

McCarthy, Blaine G; Pearson, Ryan M; Lim, Chern-Hooi; Sartor, Steven M; Damrauer, Niels H; Miyake, Garret M

2018-04-18

Through the study of structure-property relationships using a combination of experimental and computational analyses, a number of phenoxazine derivatives have been developed as visible light absorbing, organic photoredox catalysts (PCs) with excited state reduction potentials rivaling those of highly reducing transition metal PCs. Time-dependent density functional theory (TD-DFT) computational modeling of the photoexcitation of N-aryl and core modified phenoxazines guided the design of PCs with absorption profiles in the visible regime. In accordance with our previous work with N, N-diaryl dihydrophenazines, characterization of noncore modified N-aryl phenoxazines in the excited state demonstrated that the nature of the N-aryl substituent dictates the ability of the PC to access a charge transfer excited state. However, our current analysis of core modified phenoxazines revealed that these molecules can access a different type of CT excited state which we posit involves a core substituent as the electron acceptor. Modification of the core of phenoxazine derivatives with electron-donating and electron-withdrawing substituents was used to alter triplet energies, excited state reduction potentials, and oxidation potentials of the phenoxazine derivatives. The catalytic activity of these molecules was explored using organocatalyzed atom transfer radical polymerization (O-ATRP) for the synthesis of poly(methyl methacrylate) (PMMA) using white light irradiation. All of the derivatives were determined to be suitable PCs for O-ATRP as indicated by a linear growth of polymer molecular weight as a function of monomer conversion and the ability to synthesize PMMA with moderate to low dispersity (dispersity less than or equal to 1.5) and initiator efficiencies typically greater than 70% at high conversions. However, only PCs that exhibit strong absorption of visible light and strong triplet excited state reduction potentials maintain control over the polymerization during the entire course of the reaction. The structure-property relationships established here will enable the application of these organic PCs for O-ATRP and other photoredox-catalyzed small molecule and polymer syntheses.

Mathematical learning instruction and teacher motivation factors affecting science technology engineering and math (STEM) major choices in 4-year colleges and universities: Multilevel structural equation modeling

NASA Astrophysics Data System (ADS)

Lee, Ahlam

2011-12-01

Using the Educational Longitudinal Study of 2002/06, this study examined the effects of the selected mathematical learning and teacher motivation factors on graduates' science, technology, engineering, and math (STEM) related major choices in 4-year colleges and universities, as mediated by math performance and math self-efficacy. Using multilevel structural equation modeling, I analyzed: (1) the association between mathematical learning instruction factors (i.e., computer, individual, and lecture-based learning activities in mathematics) and students' STEM major choices in 4-year colleges and universities as mediated by math performance and math self-efficacy and (2) the association between school factor, teacher motivation and students' STEM major choices in 4-year colleges and universities via mediators of math performance and math self-efficacy. The results revealed that among the selected learning experience factors, computer-based learning activities in math classrooms yielded the most positive effects on math self-efficacy, which significantly predicted the increase in the proportion of students' STEM major choice as mediated by math self-efficacy. Further, when controlling for base-year math Item Response Theory (IRT) scores, a positive relationship between individual-based learning activities in math classrooms and the first follow-up math IRT scores emerged, which related to the high proportion of students' STEM major choices. The results also indicated that individual and lecture-based learning activities in math yielded positive effects on math self-efficacy, which related to STEM major choice. Concerning between-school levels, teacher motivation yielded positive effects on the first follow up math IRT score, when controlling for base year IRT score. The results from this study inform educators, parents, and policy makers on how mathematics instruction can improve student math performance and encourage more students to prepare for STEM careers. Students should receive all possible opportunities to use computers to enhance their math self-efficacy, be encouraged to review math materials, and concentrate on listening to math teachers' lectures. While all selected math-learning activities should be embraced in math instruction, computer and individual-based learning activities, which reflect student-driven learning, should be emphasized in the high school instruction. Likewise, students should be encouraged to frequently engage in individual-based learning activities to improve their math performance.

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

Characterizing the structure-function relationship reveals the mode of action of a novel antimicrobial peptide, P1, from jumper ant Myrmecia pilosula.

PubMed

Tseng, Tien-Sheng; Tsai, Keng-Chang; Chen, Chinpan

2017-06-01

Microbial infections of antibiotic-resistant strains cause serious diseases and have a significant impact on public health worldwide, so novel antimicrobial drugs are urgently needed. Insect venoms, a rich source of bioactive components containing antimicrobial peptides (AMPs), are attractive candidates for new therapeutic agents against microbes. Recently, a novel peptide, P1, identified from the venom of the Australian jumper ant Myrmecia pilosula, showed potent antimicrobial activities against both Gram-negative and Gram-positive bacteria, but its structure-function relationship is unknown. Here, we used biochemical and biophysical techniques coupled with computational simulations to explore the mode of action of P1 interaction with dodecylphosphocholine (DPC) micelles as a model membrane system. Our circular dichroism (CD) and NMR studies revealed an amphipathic α-helical structure for P1 upon interaction with DPC micelles. A paramagnetic relaxation enhancement approach revealed that P1 orients its α-helix segment (F6-G14) into DPC micelles. In addition, the α-helix segment could be essential for membrane permeabilization and antimicrobial activity. Moreover, the arginine residues R8, R11, and R15 significantly contribute to helix formation and membrane-binding affinity. The lysine residue K19 of the C-terminus functionally guides P1 to interact with DPC micelles in the early interaction stage. Our study provides insights into the mode of action of P1, which is valuable in modifying and developing potent AMPs as antibiotic drugs.

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Advanced thermally stable jet fuels. Technical progress report, January 1995--March 1995

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

Schobert, H.H.; Eser, S.; Song, C.

Quantitative structure-property relationships have been applied to study the thermal stability of pure hydrocarbons typical of jet fuel components. A simple method of chemical structure description in terms of Benson groups was tested in searching for structure-property relationships for the hydrocarbons tested experimentally in this program. Molecular connectivity as a structure-based approach to chemical structure-property relationship analysis was also tested. Further development of both the experimental data base and computational methods will be necessary. Thermal decomposition studies, using glass tube reactors, were extended to two additional model compounds: n-decane and n-dodecane. Efforts on refining the deposit growth measurement and characterizationmore » of suspended matter in stressed fuels have lead to improvements in the analysis of stressed fuels. Catalytic hydrogenation and dehydrogenation studies utilizing a molybdenum sulfide catalyst are also described.« less

The Social Organization of the Computer Underground

DTIC Science & Technology

1989-08-01

colleagues, with only small groups approaching peer relationships. 14 . SUBJECT TERMS HACK, Computer Underground 15. NUMBER OF PAGES 16. PRICE CODE 17...between individuals involved in a common activity (pp. 13- 14 ). Assessing the degree and manner in which the...criminalized over the past several years . Hackers, and the "danger" that they present in our computer dependent

Large-scale structural analysis: The structural analyst, the CSM Testbed and the NAS System

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Mccleary, Susan L.; Macy, Steven C.; Aminpour, Mohammad A.

1989-01-01

The Computational Structural Mechanics (CSM) activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM testbed methods development environment is presented and some numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

Integrating Mathematical Modeling for Undergraduate Pre-Service Science Education Learning and Instruction in Middle School Classrooms

ERIC Educational Resources Information Center

Carrejo, David; Robertson, William H.

2011-01-01

Computer-based mathematical modeling in physics is a process of constructing models of concepts and the relationships between them in the scientific characteristics of work. In this manner, computer-based modeling integrates the interactions of natural phenomenon through the use of models, which provide structure for theories and a base for…

Impaired Oral Reading in Two Atypical Dyslexics: A Comparison with a Computational Lexical-Analogy Model

ERIC Educational Resources Information Center

Marchand, Y.; Friedman, R.B.

2005-01-01

A computational model of reading was developed based upon the notion that the structural relationship between orthography and phonology is of greater importance than the dimension of semantics for the reading aloud of single words. Degradation of this model successfully simulated the reading performance of two patients with atypical acquired…

Structure-activity relationships of selected phenazines against Mycobacterium leprae in vitro.

PubMed Central

Franzblau, S G; O'Sullivan, J F

1988-01-01

Structure-activity relationships of phenazines against Mycobacterium leprae were investigated by using an in vitro radiorespirometric assay. In general, activity in ascending order was observed in compounds containing no chlorine atoms, a monochlorinated phenazine nucleus, and chlorines in the para positions of both the anilino and phenyl rings. The most active compounds contained a 2,2,6,6-tetramethylpiperidine substitution at the imino nitrogen. Most of these chlorinated phenazines were considerably more active in vitro than clofazimine (B663). PMID:3056241

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments.

PubMed

Card, Marcella L; Gomez-Alvarez, Vicente; Lee, Wen-Hsiung; Lynch, David G; Orentas, Nerija S; Lee, Mari Titcombe; Wong, Edmund M; Boethling, Robert S

2017-03-22

Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21 st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19 th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20 th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.

An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project.

PubMed

Brehm, Martin; Kafka, Alexander; Bamler, Markus; Kühne, Ralph; Schüürmann, Gerrit; Sikk, Lauri; Burk, Jaanus; Burk, Peeter; Tamm, Tarmo; Tämm, Kaido; Pokhrel, Suman; Mädler, Lutz; Kahru, Anne; Aruoja, Villem; Sihtmäe, Mariliis; Scott-Fordsmand, Janeck; Sorensen, Peter B; Escorihuela, Laura; Roca, Carlos P; Fernández, Alberto; Giralt, Francesc; Rallo, Robert

2017-01-01

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

PubMed

Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

2004-11-21

Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

QSAR modeling: where have you been? Where are you going to?

PubMed

Cherkasov, Artem; Muratov, Eugene N; Fourches, Denis; Varnek, Alexandre; Baskin, Igor I; Cronin, Mark; Dearden, John; Gramatica, Paola; Martin, Yvonne C; Todeschini, Roberto; Consonni, Viviana; Kuz'min, Victor E; Cramer, Richard; Benigni, Romualdo; Yang, Chihae; Rathman, James; Terfloth, Lothar; Gasteiger, Johann; Richard, Ann; Tropsha, Alexander

2014-06-26

Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.

QSAR Modeling: Where have you been? Where are you going to?

PubMed Central

Cherkasov, Artem; Muratov, Eugene N.; Fourches, Denis; Varnek, Alexandre; Baskin, Igor I.; Cronin, Mark; Dearden, John; Gramatica, Paola; Martin, Yvonne C.; Todeschini, Roberto; Consonni, Viviana; Kuz'min, Victor E.; Cramer, Richard; Benigni, Romualdo; Yang, Chihae; Rathman, James; Terfloth, Lothar; Gasteiger, Johann; Richard, Ann; Tropsha, Alexander

2014-01-01

Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss: (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists towards collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making. PMID:24351051

A socioeconomic related 'digital divide' exists in how, not if, young people use computers.

PubMed

Harris, Courtenay; Straker, Leon; Pollock, Clare

2017-01-01

Government initiatives have tried to ensure uniform computer access for young people; however a divide related to socioeconomic status (SES) may still exist in the nature of information technology (IT) use. This study aimed to investigate this relationship in 1,351 Western Australian children between 6 and 17 years of age. All participants had computer access at school and 98.9% at home. Neighbourhood SES was related to computer use, IT activities, playing musical instruments, and participating in vigorous physical activity. Participants from higher SES neighbourhoods were more exposed to school computers, reading, playing musical instruments, and vigorous physical activity. Participants from lower SES neighbourhoods were more exposed to TV, electronic games, mobile phones, and non-academic computer activities at home. These patterns may impact future economic, academic, and health outcomes. Better insight into neighbourhood SES influences will assist in understanding and managing the impact of computer use on young people's health and development.

A socioeconomic related 'digital divide' exists in how, not if, young people use computers

PubMed Central

2017-01-01

Government initiatives have tried to ensure uniform computer access for young people; however a divide related to socioeconomic status (SES) may still exist in the nature of information technology (IT) use. This study aimed to investigate this relationship in 1,351 Western Australian children between 6 and 17 years of age. All participants had computer access at school and 98.9% at home. Neighbourhood SES was related to computer use, IT activities, playing musical instruments, and participating in vigorous physical activity. Participants from higher SES neighbourhoods were more exposed to school computers, reading, playing musical instruments, and vigorous physical activity. Participants from lower SES neighbourhoods were more exposed to TV, electronic games, mobile phones, and non-academic computer activities at home. These patterns may impact future economic, academic, and health outcomes. Better insight into neighbourhood SES influences will assist in understanding and managing the impact of computer use on young people’s health and development. PMID:28362868

Partitioning and lipophilicity in quantitative structure-activity relationships.

PubMed Central

Dearden, J C

1985-01-01

The history of the relationship of biological activity to partition coefficient and related properties is briefly reviewed. The dominance of partition coefficient in quantitation of structure-activity relationships is emphasized, although the importance of other factors is also demonstrated. Various mathematical models of in vivo transport and binding are discussed; most of these involve partitioning as the primary mechanism of transport. The models describe observed quantitative structure-activity relationships (QSARs) well on the whole, confirming that partitioning is of key importance in in vivo behavior of a xenobiotic. The partition coefficient is shown to correlate with numerous other parameters representing bulk, such as molecular weight, volume and surface area, parachor and calculated indices such as molecular connectivity; this is especially so for apolar molecules, because for polar molecules lipophilicity factors into both bulk and polar or hydrogen bonding components. The relationship of partition coefficient to chromatographic parameters is discussed, and it is shown that such parameters, which are often readily obtainable experimentally, can successfully supplant partition coefficient in QSARs. The relationship of aqueous solubility with partition coefficient is examined in detail. Correlations are observed, even with solid compounds, and these can be used to predict solubility. The additive/constitutive nature of partition coefficient is discussed extensively, as are the available schemes for the calculation of partition coefficient. Finally the use of partition coefficient to provide structural information is considered. It is shown that partition coefficient can be a valuable structural tool, especially if the enthalpy and entropy of partitioning are available. PMID:3905374

PACS—Realization of an adaptive concept using pressure actuated cellular structures

NASA Astrophysics Data System (ADS)

Gramüller, B.; Boblenz, J.; Hühne, C.

2014-10-01

A biologically inspired concept is investigated which can be utilized to develop energy efficient, lightweight and applicational flexible adaptive structures. Building a real life morphing unit is an ambitious task as the numerous works in the particular field show. Summarizing fundamental demands and barriers regarding shape changing structures, the basic challenges of designing morphing structures are listed. The concept of Pressure Actuated Cellular Structures (PACS) is arranged within the recent morphing activities and it is shown that it complies with the underlying demands. Systematically divided into energy-related and structural subcomponents the working principle is illuminated and relationships between basic design parameters are expressed. The analytical background describing the physical mechanisms of PACS is presented in concentrated manner. This work focuses on the procedure of dimensioning, realizing and experimental testing of a single cell and a single row cantilever made of PACS. The experimental outcomes as well as the results from the FEM computations are used for evaluating the analytical methods. The functionality of the basic principle is thus validated and open issues are determined pointing the way ahead.

Evaluating a Model of Youth Physical Activity

ERIC Educational Resources Information Center

Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary

2010-01-01

Objective: To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods: Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a…

Development of Novel Repellents Using Structure - Activity Modeling of Compounds in the USDA Archival Database

DTIC Science & Technology

2011-01-01

used in efforts to develop QSAR models. Measurement of Repellent Efficacy Screening for Repellency of Compounds with Unknown Toxicology In screening...CPT) were used to develop Quantitative Structure Activity Relationship ( QSAR ) models to predict repellency. Successful prediction of novel...acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not

Hot and Spicy versus Cool and Minty as an Example of Organic Structure-Activity Relationships

NASA Astrophysics Data System (ADS)

Kimbrough, Doris R.

1997-07-01

There are two classes of substances that activate neural receptors that are involved in temperature perception. Structures of substances found in spices and food that we normally associate with "hot" (or spicy) and "cool" (or minty) flavors are presented and discussed. Functional group similarities within the two groups provide an interesting example of the relationship between molecular structure and molecular function in organic chemistry.

Toll-like receptor 4-related immunostimulatory polysaccharides: Primary structure, activity relationships, and possible interaction models.

PubMed

Zhang, Xiaorui; Qi, Chunhui; Guo, Yan; Zhou, Wenxia; Zhang, Yongxiang

2016-09-20

Toll-like receptor (TLR) 4 is an important polysaccharide receptor; however, the relationships between the structures and biological activities of TLR4 and polysaccharides remain unknown. Many recent findings have revealed the primary structure of TLR4/MD-2-related polysaccharides, and several three-dimensional structure models of polysaccharide-binding proteins have been reported; and these models provide insights into the mechanisms through which polysaccharides interact with TLR4. In this review, we first discuss the origins of polysaccharides related to TLR4, including polysaccharides from higher plants, fungi, bacteria, algae, and animals. We then briefly describe the glucosidic bond types of TLR4-related heteroglycans and homoglycans and describe the typical molecular weights of TLR4-related polysaccharides. The primary structures and activity relationships of polysaccharides with TLR4/MD-2 are also discussed. Finally, based on the existing interaction models of LPS with TLR4/MD-2 and linear polysaccharides with proteins, we provide insights into the possible interaction models of polysaccharide ligands with TLR4/MD-2. To our knowledge, this review is the first to summarize the primary structures and activity relationships of TLR4-related polysaccharides and the possible mechanisms of interaction for TLR4 and TLR4-related polysaccharides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structure-activity relationship of the ionic cocrystal: 5-amino-2-naphthalene sulfonate·ammonium ions for pharmaceutical applications

NASA Astrophysics Data System (ADS)

Sangeetha, M.; Mathammal, R.

2018-02-01

The ionic cocrystals of 5-amino-2-naphthalene sulfonate · ammonium ions (ANSA-ṡNH4+) were grown under slow evaporation method and examined in detail for pharmaceutical applications. The crystal structure and intermolecular interactions were studied from the single X-ray diffraction analysis and the Hirshfeld surfaces. The 2D fingerprint plots displayed the inter-contacts possible in the ionic crystal. Computational DFT method was established to determine the structural, physical and chemical properties. The molecular geometries obtained from the X-ray studies were compared with the optimized geometrical parameters calculated using DFT/6-31 + G(d,p) method. The band gap energy calculated from the UV-Visible spectral analysis and the HOMO-LUMO energy gap are compared. The theoretical UV-Visible calculations helped in determining the type of electronic transition taking place in the title molecule. The maximum absorption bands and transitions involved in the molecule represented the drug reaction possible. Non-linear optical properties were characterized from SHG efficiency measurements experimentally and the NLO parameters are also calculated from the optimized structure. The reactive sites within the molecule are detailed from the MEP surface maps. The molecular docking studies evident the structure-activity of the ionic cocrystal for anti-cancer drug property.

Research and development program for the development of advanced time-temperature dependent constitutive relationships. Volume 2: Programming manual

NASA Technical Reports Server (NTRS)

Cassenti, B. N.

1983-01-01

The results of a 10-month research and development program for nonlinear structural modeling with advanced time-temperature constitutive relationships are presented. The implementation of the theory in the MARC nonlinear finite element code is discussed, and instructions for the computational application of the theory are provided.

Hyper-polyhedron model applied to molecular screening of guanidines as Na/H exchange inhibitors.

PubMed

Bao, Xin-Hua; Lu, Wen-Cong; Liu, Liang; Chen, Nian-Yi

2003-05-01

To investigate structure-activity relationships of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines in Na/H exchange inhibitory activities and probe into a new method of the computer-aided molecular screening. The hyper-polyhedron model (HPM) was proposed in our lab. The samples with probably higher activities could be determined in such a way that their representing points should be in the hyper-polyhedron region where all known samples with high activities were distributed. And the predictive ability of different methods available was tested by the cross-validation experiment. The accurate rate of molecular screening of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines by HPM was much higher than that obtained by PCA (principal component analysis) and Fisher methods for the data set available here. Therefore, HPM could be used as a powerful tool for screening new compounds with probably higher activities.

Synergistic Interplay of Medicinal Chemistry and Formulation Strategies in Nanotechnology - From Drug Discovery to Nanocarrier Design and Development.

PubMed

Sunoqrot, Suhair; Hamed, Rania; Abdel-Halim, Heba; Tarawneh, Ola

2017-01-01

Over the last few decades, nanotechnology has given rise to promising new therapies and diagnostic tools for a wide range of diseases, especially cancer. The unique properties of nanocarriers such as liposomes, polymeric nanoparticles, micelles, and bioconjugates have mainly been exploited to enhance drug solubility, dissolution, and bioavailability. The most important advantage offered by nanotechnology is the ability to specifically target organs, tissues, and individual cells, which ultimately reduces the systemic side effects and improves the therapeutic index of drug molecules. The contribution of medicinal chemistry to nanotechnology is evident in the abundance of new active molecules that are being discovered but are faced with tremendous delivery challenges by conventional formulation strategies. Additionally, medicinal chemistry plays a crucial role in all the steps involved in the preparation of nanocarriers, where structure-activity relationships of the drug molecule as well as the nanocarrier are harnessed to enhance the design, efficacy, and safety of nanoformulations. The aim of this review is to provide an overview of the contributions of medicinal chemistry to nanotechnology, from supplying drug candidates and inspiring high-throughput nanocarrier design strategies, to structure-activity relationship elucidation and construction of computational models for better understanding of nanocarrier physicochemical properties and biological behavior. These two fields are undoubtedly interconnected and we will continue to see the fruits of that communion for years to come. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Context-Aware Ubiquitous Learning Approach for Providing Instant Learning Support in Personal Computer Assembly Activities

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen

2014-01-01

Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…

Identifying Metabolically Active Chemicals Using a Consensus ...

EPA Pesticide Factsheets

Traditional toxicity testing provides insight into the mechanisms underlying toxicological responses but requires a high investment in a large number of resources. The new paradigm of testing approaches involves rapid screening studies able to evaluate thousands of chemicals across hundreds of biological targets through use of in vitro assays. Endocrine disrupting chemicals (EDCs) are of concern due to their ability to alter neurodevelopment, behavior, and reproductive success of humans and other species. A recent integrated computational model examined results across 18 ER-related assays in the ToxCast in vitro screening program to eliminate chemicals that produce a false signal by possibly interfering with the technological attributes of an individual assay. However, in vitro assays can also lead to false negatives when the complex metabolic processes that render a chemical bioactive in a living system might be unable to be replicated in an in vitro environment. In the current study, the influence of metabolism was examined for over 1,400 chemicals considered inactive using the integrated computational model. Over 2,000 first-generation and over 4,000 second-generation metabolites were generated for the inactive chemicals using in silico techniques. Next, a consensus model comprised of individual structure activity relationship (SAR) models was used to predict ER-binding activity for each of the metabolites. Binding activity was predicted for 8-10% of the meta

Scaffolding of Small Groups' Metacognitive Activities with an Avatar

ERIC Educational Resources Information Center

Molenaar, Inge; Chiu, Ming Ming; Sleegers, Peter; van Boxtel, Carla

2011-01-01

Metacognitive scaffolding in a computer-supported learning environment can influence students' metacognitive activities, metacognitive knowledge and domain knowledge. In this study we analyze how metacognitive activities mediate the relationships between different avatar scaffolds on students' learning. Multivariate, multilevel analysis of the…

A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.

PubMed

Zhu, Hao; Ye, Lin; Richard, Ann; Golbraikh, Alexander; Wright, Fred A; Rusyn, Ivan; Tropsha, Alexander

2009-08-01

Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public-private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC(50)) and in vivo rodent median lethal dose (LD(50)) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure-activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD(50) values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC(50) and LD(50). However, a linear IC(50) versus LD(50) correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC(50) and LD(50) values: One group comprises compounds with linear IC(50) versus LD(50) relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k-nearest neighbor continuous QSAR models for each subclass to predict LD(50) values from chemical descriptors. All models were extensively validated using special protocols. The novelty of this modeling approach is that it uses the relationships between in vivo and in vitro data only to inform the initial construction of the hierarchical two-step QSAR models. Models resulting from this approach employ chemical descriptors only for external prediction of acute rodent toxicity.

The power of an ontology-driven developmental toxicity database for data mining and computational modeling

EPA Science Inventory

Modeling of developmental toxicology presents a significant challenge to computational toxicology due to endpoint complexity and lack of data coverage. These challenges largely account for the relatively few modeling successes using the structure–activity relationship (SAR) parad...

Multidisciplinary analysis of actively controlled large flexible spacecraft

NASA Technical Reports Server (NTRS)

Cooper, Paul A.; Young, John W.; Sutter, Thomas R.

1986-01-01

The control of Flexible Structures (COFS) program has supported the development of an analysis capability at the Langley Research Center called the Integrated Multidisciplinary Analysis Tool (IMAT) which provides an efficient data storage and transfer capability among commercial computer codes to aid in the dynamic analysis of actively controlled structures. IMAT is a system of computer programs which transfers Computer-Aided-Design (CAD) configurations, structural finite element models, material property and stress information, structural and rigid-body dynamic model information, and linear system matrices for control law formulation among various commercial applications programs through a common database. Although general in its formulation, IMAT was developed specifically to aid in the evaluation of the structures. A description of the IMAT system and results of an application of the system are given.

Application of Quantitative Structure–Activity Relationship Models of 5-HT1A Receptor Binding to Virtual Screening Identifies Novel and Potent 5-HT1A Ligands

PubMed Central

2015-01-01

The 5-hydroxytryptamine 1A (5-HT1A) serotonin receptor has been an attractive target for treating mood and anxiety disorders such as schizophrenia. We have developed binary classification quantitative structure–activity relationship (QSAR) models of 5-HT1A receptor binding activity using data retrieved from the PDSP Ki database. The prediction accuracy of these models was estimated by external 5-fold cross-validation as well as using an additional validation set comprising 66 structurally distinct compounds from the World of Molecular Bioactivity database. These validated models were then used to mine three major types of chemical screening libraries, i.e., drug-like libraries, GPCR targeted libraries, and diversity libraries, to identify novel computational hits. The five best hits from each class of libraries were chosen for further experimental testing in radioligand binding assays, and nine of the 15 hits were confirmed to be active experimentally with binding affinity better than 10 μM. The most active compound, Lysergol, from the diversity library showed very high binding affinity (Ki) of 2.3 nM against 5-HT1A receptor. The novel 5-HT1A actives identified with the QSAR-based virtual screening approach could be potentially developed as novel anxiolytics or potential antischizophrenic drugs. PMID:24410373

The cerebral control of speech tempo: opposite relationship between speaking rate and BOLD signal changes at striatal and cerebellar structures.

PubMed

Riecker, Axel; Kassubek, Jan; Gröschel, Klaus; Grodd, Wolfgang; Ackermann, Hermann

2006-01-01

So far, only sparse data on the cerebral organization of speech motor control are available. In order to further delineate the neural basis of articulatory functions, fMRI measurements were performed during self-paced syllable repetitions at six different frequencies (2-6 Hz). Bilateral hemodynamic main effects, calculated across all syllable rates considered, emerged within sensorimotor cortex, putamen, thalamus and cerebellum. At the level of the caudatum and the anterior insula, activation was found restricted to the left side. The computation of rate-to-response functions of the BOLD signal revealed a negative linear relationship between syllable frequency and response magnitude within the striatum whereas cortical areas and cerebellar hemispheres exhibited an opposite activation pattern. Dysarthric patients with basal ganglia disorders show unimpaired or even accelerated speaking rate whereas, in contrast, cerebellar dysfunctions give rise to slowed speech tempo which does not fall below a rate of about 3 Hz. The observed rate-to-response profiles of the BOLD signal thus might help to elucidate the pathophysiological mechanisms of dysarthric deficits in central motor disorders.

Defining the molecular structure of teixobactin analogues and understanding their role in antibacterial activities.

PubMed

Parmar, Anish; Prior, Stephen H; Iyer, Abhishek; Vincent, Charlotte S; Van Lysebetten, Dorien; Breukink, Eefjan; Madder, Annemieke; Taylor, Edward J; Singh, Ishwar

2017-02-07

The discovery of the highly potent antibiotic teixobactin, which kills the bacteria without any detectable resistance, has stimulated interest in its structure-activity relationship. However, a molecular structure-activity relationship has not been established so far for teixobactin. Moreover, the importance of the individual amino acids in terms of their l/d configuration and their contribution to the molecular structure and biological activity are still unknown. For the first time, we have defined the molecular structure of seven teixobactin analogues through the variation of the d/l configuration of its key residues, namely N-Me-d-Phe, d-Gln, d-allo-Ile and d-Thr. Furthermore, we have established the role of the individual d amino acids and correlated this with the molecular structure and biological activity. Through extensive NMR and structural calculations, including molecular dynamics simulations, we have revealed the residues for maintaining a reasonably unstructured teixobactin which is imperative for biological activity.

Structural complexities in the active layers of organic electronics.

PubMed

Lee, Stephanie S; Loo, Yueh-Lin

2010-01-01

The field of organic electronics has progressed rapidly in recent years. However, understanding the direct structure-function relationships between the morphology in electrically active layers and the performance of devices composed of these materials has proven difficult. The morphology of active layers in organic electronics is inherently complex, with heterogeneities existing across multiple length scales, from subnanometer to micron and millimeter range. A major challenge still facing the organic electronics community is understanding how the morphology across all of the length scales in active layers collectively determines the device performance of organic electronics. In this review we highlight experiments that have contributed to the elucidation of structure-function relationships in organic electronics and also point to areas in which knowledge of such relationships is still lacking. Such knowledge will lead to the ability to select active materials on the basis of their inherent properties for the fabrication of devices with prespecified characteristics.

Structure-activity relationship of karrikin germination stimulants.

PubMed

Flematti, Gavin R; Scaffidi, Adrian; Goddard-Borger, Ethan D; Heath, Charles H; Nelson, David C; Commander, Lucy E; Stick, Robert V; Dixon, Kingsley W; Smith, Steven M; Ghisalberti, Emilio L

2010-08-11

Karrikins (2H-furo[2,3-c]pyran-2-ones) are potent smoke-derived germination promoters for a diverse range of plant species but, to date, their mode of action remains unknown. This paper reports the structure-activity relationship of numerous karrikin analogues to increase understanding of the key structural features of the molecule that are required for biological activity. The results demonstrate that modification at the C5 position is preferred over modification at the C3, C4, or C7 positions for retaining the highest bioactivity.

Motivating At-Risk Students through Computer-based Cooperative Learning Activities.

ERIC Educational Resources Information Center

Gan, Siowck-Lee

1999-01-01

Malaysian at-risk students trained in information-technology skills were appointed to lead cooperative-learning groups engaged in computer-search activities. Activities were structured to incorporate individual accountability, positive interdependence and interaction, collaborative skills, and group processing. Motivation, self-confidence,…

Aquatic toxicity of acrylates and methacrylates: quantitative structure-activity relationships based on Kow and LC50

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

Reinert, K.H.

1987-12-01

Recent EPA scrutiny of acrylate and methacrylate monomers has resulted in restrictive consent orders and Significant New Use Rules under the Toxic Substances Control Act, based on structure-activity relationships using mouse skin painting studies. The concern is centered on human health issues regarding worker and consumer exposure. Environmental issues, such as aquatic toxicity, are still of concern. Understanding the relationships and environmental risks to aquatic organisms may improve the understanding of the potential risks to human health. This study evaluates the quantitative structure-activity relationships from measured log Kow's and log LC50's for Pimephales promelas (fathead minnow) and Carassius auratus (goldfish).more » Scientific support of the current regulations is also addressed. Two monomer classes were designated: acrylates and methacrylates. Spearman rank correlation and linear regression were run. Based on this study, an ecotoxicological difference exists between acrylates and methacrylates. Regulatory activities and scientific study should reflect this difference.« less

Functional Evolution of PLP-dependent Enzymes based on Active-Site Structural Similarities

PubMed Central

Catazaro, Jonathan; Caprez, Adam; Guru, Ashu; Swanson, David; Powers, Robert

2014-01-01

Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5’-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the Comparison of Protein Active Site Structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS. PMID:24920327

Functional evolution of PLP-dependent enzymes based on active-site structural similarities.

PubMed

Catazaro, Jonathan; Caprez, Adam; Guru, Ashu; Swanson, David; Powers, Robert

2014-10-01

Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5'-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the comparison of protein active site structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional-fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS. © 2014 Wiley Periodicals, Inc.

Differential modulation of FXR activity by chlorophacinone and ivermectin analogs

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

Hsu, Chia-Wen

Chemicals that alter normal function of farnesoid X receptor (FXR) have been shown to affect the homeostasis of bile acids, glucose, and lipids. Several structural classes of environmental chemicals and drugs that modulated FXR transactivation were previously identified by quantitative high-throughput screening (qHTS) of the Tox21 10 K chemical collection. In the present study, we validated the FXR antagonist activity of selected structural classes, including avermectin anthelmintics, dihydropyridine calcium channel blockers, 1,3-indandione rodenticides, and pyrethroid pesticides, using in vitro assay and quantitative structural-activity relationship (QSAR) analysis approaches. (Z)-Guggulsterone, chlorophacinone, ivermectin, and their analogs were profiled for their ability to altermore » CDCA-mediated FXR binding using a panel of 154 coregulator motifs and to induce or inhibit transactivation and coactivator recruitment activities of constitutive androstane receptor (CAR), liver X receptor alpha (LXRα), or pregnane X receptor (PXR). Our results showed that chlorophacinone and ivermectin had distinct modes of action (MOA) in modulating FXR-coregulator interactions and compound selectivity against the four aforementioned functionally-relevant nuclear receptors. These findings collectively provide mechanistic insights regarding compound activities against FXR and possible explanations for in vivo toxicological observations of chlorophacinone, ivermectin, and their analogs. - Highlights: • A subset of Tox21 chemicals was investigated for FXR antagonism. • In vitro and computational approaches were used to evaluate FXR antagonists. • Chlorophacinone and ivermectin had distinct patterns in modulating FXR activity.« less

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.

Encoding techniques for complex information structures in connectionist systems

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

Two general information encoding techniques called relative position encoding and pattern similarity association are presented. They are claimed to be a convenient basis for the connectionist implementation of complex, short term information processing of the sort needed in common sense reasoning, semantic/pragmatic interpretation of natural language utterances, and other types of high level cognitive processing. The relationships of the techniques to other connectionist information-structuring methods, and also to methods used in computers, are discussed in detail. The rich inter-relationships of these other connectionist and computer methods are also clarified. The particular, simple forms are discussed that the relative position encoding and pattern similarity association techniques take in the author's own connectionist system, called Conposit, in order to clarify some issues and to provide evidence that the techniques are indeed useful in practice.

Elucidating quantitative stability/flexibility relationships within thioredoxin and its fragments using a distance constraint model.

PubMed

Jacobs, Donald J; Livesay, Dennis R; Hules, Jeremy; Tasayco, Maria Luisa

2006-05-05

Numerous quantitative stability/flexibility relationships, within Escherichia coli thioredoxin (Trx) and its fragments are determined using a minimal distance constraint model (DCM). A one-dimensional free energy landscape as a function of global flexibility reveals Trx to fold in a low-barrier two-state process, with a voluminous transition state. Near the folding transition temperature, the native free energy basin is markedly skewed to allow partial unfolded forms. Under native conditions the skewed shape is lost, and the protein forms a compact structure with some flexibility. Predictions on ten Trx fragments are generally consistent with experimental observations that they are disordered, and that complementary fragments reconstitute. A hierarchical unfolding pathway is uncovered using an exhaustive computational procedure of breaking interfacial cross-linking hydrogen bonds that span over a series of fragment dissociations. The unfolding pathway leads to a stable core structure (residues 22-90), predicted to act as a kinetic trap. Direct connection between degree of rigidity within molecular structure and non-additivity of free energy is demonstrated using a thermodynamic cycle involving fragments and their hierarchical unfolding pathway. Additionally, the model provides insight about molecular cooperativity within Trx in its native state, and about intermediate states populating the folding/unfolding pathways. Native state cooperativity correlation plots highlight several flexibly correlated regions, giving insight into the catalytic mechanism that facilitates access to the active site disulfide bond. Residual native cooperativity correlations are present in the core substructure, suggesting that Trx can function when it is partly unfolded. This natively disordered kinetic trap, interpreted as a molten globule, has a wide temperature range of metastability, and it is identified as the "slow intermediate state" observed in kinetic experiments. These computational results are found to be in overall agreement with a large array of experimental data.

Numerical simulation on the adaptation of forms in trabecular bone to mechanical disuse and basic multi-cellular unit activation threshold at menopause

NASA Astrophysics Data System (ADS)

Gong, He; Fan, Yubo; Zhang, Ming

2008-04-01

The objective of this paper is to identify the effects of mechanical disuse and basic multi-cellular unit (BMU) activation threshold on the form of trabecular bone during menopause. A bone adaptation model with mechanical- biological factors at BMU level was integrated with finite element analysis to simulate the changes of trabecular bone structure during menopause. Mechanical disuse and changes in the BMU activation threshold were applied to the model for the period from 4 years before to 4 years after menopause. The changes in bone volume fraction, trabecular thickness and fractal dimension of the trabecular structures were used to quantify the changes of trabecular bone in three different cases associated with mechanical disuse and BMU activation threshold. It was found that the changes in the simulated bone volume fraction were highly correlated and consistent with clinical data, and that the trabecular thickness reduced significantly during menopause and was highly linearly correlated with the bone volume fraction, and that the change trend of fractal dimension of the simulated trabecular structure was in correspondence with clinical observations. The numerical simulation in this paper may help to better understand the relationship between the bone morphology and the mechanical, as well as biological environment; and can provide a quantitative computational model and methodology for the numerical simulation of the bone structural morphological changes caused by the mechanical environment, and/or the biological environment.

Failure Analysis in Platelet Molded Composite Systems

NASA Astrophysics Data System (ADS)

Kravchenko, Sergii G.

Long-fiber discontinuous composite systems in the form of chopped prepreg tapes provide an advanced, structural grade, molding compound allowing for fabrication of complex three-dimensional components. Understanding of process-structure-property relationship is essential for application of prerpeg platelet molded components, especially because of their possible irregular disordered heterogeneous morphology. Herein, a structure-property relationship was analyzed in the composite systems of many platelets. Regular and irregular morphologies were considered. Platelet-based systems with more ordered morphology possess superior mechanical performance. While regular morphologies allow for a careful inspection of failure mechanisms derived from the morphological characteristics, irregular morphologies are representative of the composite architectures resulting from uncontrolled deposition and molding with chopped prerpegs. Progressive failure analysis (PFA) was used to study the damaged deformation up to ultimate failure in a platelet-based composite system. Computational damage mechanics approaches were utilized to conduct the PFA. The developed computational models granted understanding of how the composite structure details, meaning the platelet geometry and system morphology (geometrical arrangement and orientation distribution of platelets), define the effective mechanical properties of a platelet-molded composite system, its stiffness, strength and variability in properties.

Health-Related Physical Fitness, BMI, physical activity and time spent at a computer screen in 6 and 7-year-old children from rural areas in Poland.

PubMed

Cieśla, Elżbieta; Mleczko, Edward; Bergier, Józef; Markowska, Małgorzata; Nowak-Starz, Grażyna

2014-01-01

The objective of the study was determination of the effect of various forms of physical activity, BMI, and time devoted to computer games on the level of Health-Related Physical Fitness (H-RF) in 6-7-year-old children from Polish rural areas. The study covered 25,816 children aged 6-7: 12,693 girls and 13,123 boys. The evaluations included body height and weight, and 4 H-RF fitness components (trunk strength, explosive leg power, arm strength and flexibility). The BMI was calculated for each child. The Questionnaire directed to parents was designed to collect information concerning the time devoted by children to computer games, spontaneous and additional physical activity. The strength of the relationships between dependent and independent variables was determined using the Spearman's rank correlation (RSp), and the relationship by using the regression analysis. The BMI negatively affected the level of all the H-RF components analysed (p=0.000). The negative effect of computer games revealed itself only with respect to flexibility (p=0.000), explosive leg power (p=0.000) and trunk muscle strength (p=0.000). A positive effect of spontaneous activity was observed for flexibility (p=0.047), explosive leg power (p=0.000), and arm strength (p=0.000). Additional activity showed a positive relationship with trunk muscles strength (p=0.000), and explosive leg power (p=0.000). The results of studies suggest that it is necessary to pay attention to the prevention of diseases related with the risk of obesity and overweight among Polish rural children as early as at pre-school age. There is also a need during education for shaping in these children the awareness of concern about own body, and the need for active participation in various forms of physical activity.

Optical Symbolic Computing

NASA Astrophysics Data System (ADS)

Neff, John A.

1989-12-01

Experiments originating from Gestalt psychology have shown that representing information in a symbolic form provides a more effective means to understanding. Computer scientists have been struggling for the last two decades to determine how best to create, manipulate, and store collections of symbolic structures. In the past, much of this struggling led to software innovations because that was the path of least resistance. For example, the development of heuristics for organizing the searching through knowledge bases was much less expensive than building massively parallel machines that could search in parallel. That is now beginning to change with the emergence of parallel architectures which are showing the potential for handling symbolic structures. This paper will review the relationships between symbolic computing and parallel computing architectures, and will identify opportunities for optics to significantly impact the performance of such computing machines. Although neural networks are an exciting subset of massively parallel computing structures, this paper will not touch on this area since it is receiving a great deal of attention in the literature. That is, the concepts presented herein do not consider the distributed representation of knowledge.

Comparison of measured temperatures, thermal stresses and creep residues with predictions on a built-up titanium structure

NASA Technical Reports Server (NTRS)

Jenkins, Jerald M.

1987-01-01

Temperature, thermal stresses, and residual creep stresses were studied by comparing laboratory values measured on a built-up titanium structure with values calculated from finite-element models. Several such models were used to examine the relationship between computational thermal stresses and thermal stresses measured on a built-up structure. Element suitability, element density, and computational temperature discrepancies were studied to determine their impact on measured and calculated thermal stress. The optimum number of elements is established from a balance between element density and suitable safety margins, such that the answer is acceptably safe yet is economical from a computational viewpoint. It is noted that situations exist where relatively small excursions of calculated temperatures from measured values result in far more than proportional increases in thermal stress values. Measured residual stresses due to creep significantly exceeded the values computed by the piecewise linear elastic strain analogy approach. The most important element in the computation is the correct definition of the creep law. Computational methodology advances in predicting residual stresses due to creep require significantly more viscoelastic material characterization.

Validation of clay modeling as a learning tool for the periventricular structures of the human brain.

PubMed

Akle, Veronica; Peña-Silva, Ricardo A; Valencia, Diego M; Rincón-Perez, Carlos W

2018-03-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a 3D-model from oil-based modeling clay affects learners' understanding of periventricular structures of the brain among undergraduate medical students in Colombia. Students were provided with an instructional video before building the models of the structures, and thereafter took a computer-based quiz. They then brought their clay models to class where they answered questions about the structures via interactive response cards. Their knowledge of periventricular structures was assessed with a paper-based quiz. Afterward, a focus group was conducted and a survey was distributed to understand students' perceptions of the activity, as well as the impact of the intervention on their understanding of anatomical structures in 3D. Quiz scores of students that constructed the models were significantly higher than those taught the material in a more traditional manner (P < 0.05). Moreover, the modeling activity reduced time spent studying the topic and increased understanding of spatial relationships between structures in the brain. The results demonstrated a significant difference between genders in their self-perception of their ability to contemplate and rotate structures mentally (P < 0.05). The study demonstrated that the construction of 3D clay models in combination with autonomous learning activities was a valuable and efficient learning tool in the anatomy course, and that additional models could be designed to promote deeper learning of other neuroanatomy topics. Anat Sci Educ 11: 137-145. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

Distributed Structure Searchable Toxicity

EPA Pesticide Factsheets

The Distributed Structure Searchable Toxicity (DSSTox) online resource provides high quality chemical structures and annotations in association with toxicity data. It helps to build a data foundation for improved structure-activity relationships and predictive toxicology. DSSTox publishes summarized chemical activity representations for structure-activity modeling and provides a structure browser. This tool also houses the chemical inventories for the ToxCast and Tox21 projects.

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

Structure-based design, synthesis, and biological evaluation of novel pyrrolyl aryl sulfones: HIV-1 non-nucleoside reverse transcriptase inhibitors active at nanomolar concentrations.

PubMed

Artico, M; Silvestri, R; Pagnozzi, E; Bruno, B; Novellino, E; Greco, G; Massa, S; Ettorre, A; Loi, A G; Scintu, F; La Colla, P

2000-05-04

Pyrrolyl aryl sulfones (PASs) have been recently reported as a new class of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) inhibitors acting at the non-nucleoside binding site of this enzyme (Artico, M.; et al. J. Med. Chem. 1996, 39, 522-530). Compound 3, the most potent inhibitor within the series (EC(50) = 0.14 microM, IC(50) = 0.4 microM, and SI > 1429), was then selected as a lead compound for a synthetic project based on molecular modeling studies. Using the three-dimensional structure of RT cocrystallized with the alpha-APA derivative R95845, we derived a model of the RT/3 complex by taking into account previously developed structure-activity relationships. Inspection of this model and docking calculations on virtual compounds prompted the design of novel PAS derivatives and related analogues. Our computational approach proved to be effective in making qualitative predictions, that is in discriminating active versus inactive compounds. Among the compounds synthesized and tested, 20 was the most active one, with EC(50) = 0.045 microM, IC(50) = 0.05 microM, and SI = 5333. Compared with the lead 3, these values represent a 3- and 8-fold improvement in the cell-based and enzyme assays, respectively, together with the highest selectivity achieved so far in the PAS series.

Synthesis, crystal structure determination, biological screening and docking studies of N1-substituted derivatives of 2,3-dihydroquinazolin-4(1H)-one as inhibitors of cholinesterases.

PubMed

Sultana, Nargis; Sarfraz, Muhammad; Tanoli, Saba Tahir; Akram, Muhammad Safwan; Sadiq, Abdul; Rashid, Umer; Tariq, Muhammad Ilyas

2017-06-01

Pursuing the strategy of developing potent AChE inhibitors, we attempted to carry out the N 1 -substitution of 2,3-dihydroquinazolin-4(1H)-one core. A set of 32 N-alkylated/benzylated quinazoline derivatives were synthesized, characterized and evaluated for their inhibition against cholinesterases. N-alkylation of the series of the compounds reported previously (N-unsubstituted) resulted in improved activity. All the compounds showed inhibition of both enzymes in the micromolar to submicromolar range. Structure activity relationship (SAR) of the 32 derivatives showed that N-benzylated compounds possess good activity than N-alkylated compounds. N-benzylated compounds 2ad and 2af were found very active with their IC 50 values toward AChE in submicromolar range (0.8µM and 0.6µM respectively). Binding modes of the synthesized compounds were explored by using GOLD (Genetic Optimization for Ligand Docking) suit v5.4.1. Computational predictions of ADMET studies reveal that all the compounds have good pharmacokinetic properties with no AMES toxicity and carcinogenicity. Moreover, all the compounds are predicted to be absorbed in human intestine and also have the ability to cross blood brain barrier. Overall, the synthesized compounds have established a structural foundation for the design of new inhibitors of cholinesterase. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of Quantum Chemical Method to Calculate Half Maximal Inhibitory Concentration (IC50 ).

PubMed

Bag, Arijit; Ghorai, Pradip Kr

2016-05-01

Till date theoretical calculation of the half maximal inhibitory concentration (IC50 ) of a compound is based on different Quantitative Structure Activity Relationship (QSAR) models which are empirical methods. By using the Cheng-Prusoff equation it may be possible to compute IC50 , but this will be computationally very expensive as it requires explicit calculation of binding free energy of an inhibitor with respective protein or enzyme. In this article, for the first time we report an ab initio method to compute IC50 of a compound based only on the inhibitor itself where the effect of the protein is reflected through a proportionality constant. By using basic enzyme inhibition kinetics and thermodynamic relations, we derive an expression of IC50 in terms of hydrophobicity, electric dipole moment (μ) and reactivity descriptor (ω) of an inhibitor. We implement this theory to compute IC50 of 15 HIV-1 capsid inhibitors and compared them with experimental results and available other QASR based empirical results. Calculated values using our method are in very good agreement with the experimental values compared to the values calculated using other methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthesis, antimicrobial activity and advances in structure-activity relationships (SARs) of novel tri-substituted thiazole derivatives.

PubMed

Reddy, Guda Mallikarjuna; Garcia, Jarem Raul; Reddy, Vemulapati Hanuman; de Andrade, Ageo Meier; Camilo, Alexandre; Pontes Ribeiro, Renan Augusto; de Lazaro, Sergio Ricardo

2016-11-10

Trisubstituted thiazoles were synthesized and studied for their antimicrobial activity and supported by theoretical calculations. In addition, MIC, MBC and MFC were also tested. Moreover, the present study was analyzed to scrutinize comprehensive structure-activity relationships. In fact, LUMO orbital energy and orbital orientation was reliable to explain their antibacterial and antifungal assay. Amongst the tested compounds, tri-methyl-substituted thiazole compound showed higher antimicrobial activity and low MIC value due to highest LUMO energy. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Computational modeling of the obstructive lung diseases asthma and COPD

PubMed Central

2014-01-01

Asthma and chronic obstructive pulmonary disease (COPD) are characterized by airway obstruction and airflow limitation and pose a huge burden to society. These obstructive lung diseases impact the lung physiology across multiple biological scales. Environmental stimuli are introduced via inhalation at the organ scale, and consequently impact upon the tissue, cellular and sub-cellular scale by triggering signaling pathways. These changes are propagated upwards to the organ level again and vice versa. In order to understand the pathophysiology behind these diseases we need to integrate and understand changes occurring across these scales and this is the driving force for multiscale computational modeling. There is an urgent need for improved diagnosis and assessment of obstructive lung diseases. Standard clinical measures are based on global function tests which ignore the highly heterogeneous regional changes that are characteristic of obstructive lung disease pathophysiology. Advances in scanning technology such as hyperpolarized gas MRI has led to new regional measurements of ventilation, perfusion and gas diffusion in the lungs, while new image processing techniques allow these measures to be combined with information from structural imaging such as Computed Tomography (CT). However, it is not yet known how to derive clinical measures for obstructive diseases from this wealth of new data. Computational modeling offers a powerful approach for investigating this relationship between imaging measurements and disease severity, and understanding the effects of different disease subtypes, which is key to developing improved diagnostic methods. Gaining an understanding of a system as complex as the respiratory system is difficult if not impossible via experimental methods alone. Computational models offer a complementary method to unravel the structure-function relationships occurring within a multiscale, multiphysics system such as this. Here we review the current state-of-the-art in techniques developed for pulmonary image analysis, development of structural models of the respiratory system and predictions of function within these models. We discuss application of modeling techniques to obstructive lung diseases, namely asthma and emphysema and the use of models to predict response to therapy. Finally we introduce a large European project, AirPROM that is developing multiscale models to investigate structure-function relationships in asthma and COPD. PMID:25471125

CERAPP: Collaborative Estrogen Receptor Activity Prediction ...

EPA Pesticide Factsheets

Humans potentially are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Many of these chemicals never have been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for assessment in costly in vivo tests, for instance, within the EPA Endocrine Disruptor Screening Program. Here, we describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating the efficacy of using predictive computational models on high-throughput screening data to screen thousands of chemicals against the ER. CERAPP combined multiple models developed in collaboration among 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1677 compounds provided by EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were tested using an evaluation set of 7522 chemicals collected from the literature. To overcome the limitations of single models, a consensus was built weighting models using a scoring function (0 to 1) based on their accuracies. Individual model scores ranged from 0.69 to 0.85, showing

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

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

Advances on Semisynthesis, Total Synthesis, and Structure-Activity Relationships of Honokiol and Magnolol Derivatives.

PubMed

Yang, Chun; Zhi, Xiaoyan; Xu, Hui

2016-01-01

Honokiol and magnolol (an isomer of honokiol) are small-molecule polyphenols isolated from the barks of Magnolia officinalis, which have been widely used in traditional Chinese and Japanese medicines. In the last decade, a variety of biological properties of honokiol and magnolol (e.g., anti-oxidativity, antitumor activity, anti-depressant activity, anti-inflammatory activity, neuroprotective activity, anti-diabetic activity, antiviral activity, and antimicrobial activity) have been reported. Meanwhile, certain mechanisms of action of some biological activities were also investigated. Moreover, many analogs of honokiol and magnolol were prepared by structural modification or total synthesis, and some exhibited very potent pharmacological activities with improved water solubility. Therefore, the present review will provide a systematic coverage on recent developments of honokiol and magnolol derivatives in regard to semisynthesis, total synthesis, and structure-activity relationships from 2000 up to now.

An overview of structure-activity relationship studies of curcumin analogs as antioxidant and anti-inflammatory agents.

PubMed

Arshad, Laiba; Haque, Md Areeful; Abbas Bukhari, Syed Nasir; Jantan, Ibrahim

2017-04-01

Curcumin, extracted mainly from Curcuma longa rhizomes, has been reported to possess potent anti-inflammatory and anti-oxidant activities. Although safe at higher doses and exhibiting multiple biological activities, curcumin still has the problem of poor bioavailability which has been an attractive area of research over the last few years. A number of efforts have been made by modifying structural features of curcumin. This review highlights the structurally modified and more stable newly synthesized curcumin analogs that have been screened against antioxidant and anti-inflammatory activities. Also the structure-activity relationship to gain insight into future guidelines for scheming new compounds has been discussed, and further these analogs being more stable may serve as promising agents for use in different pathological conditions.

The CSM testbed software system: A development environment for structural analysis methods on the NAS CRAY-2

NASA Technical Reports Server (NTRS)

Gillian, Ronnie E.; Lotts, Christine G.

1988-01-01

The Computational Structural Mechanics (CSM) Activity at Langley Research Center is developing methods for structural analysis on modern computers. To facilitate that research effort, an applications development environment has been constructed to insulate the researcher from the many computer operating systems of a widely distributed computer network. The CSM Testbed development system was ported to the Numerical Aerodynamic Simulator (NAS) Cray-2, at the Ames Research Center, to provide a high end computational capability. This paper describes the implementation experiences, the resulting capability, and the future directions for the Testbed on supercomputers.

Sequence-structure relationship study in all-α transmembrane proteins using an unsupervised learning approach.

PubMed

Esque, Jérémy; Urbain, Aurélie; Etchebest, Catherine; de Brevern, Alexandre G

2015-11-01

Transmembrane proteins (TMPs) are major drug targets, but the knowledge of their precise topology structure remains highly limited compared with globular proteins. In spite of the difficulties in obtaining their structures, an important effort has been made these last years to increase their number from an experimental and computational point of view. In view of this emerging challenge, the development of computational methods to extract knowledge from these data is crucial for the better understanding of their functions and in improving the quality of structural models. Here, we revisit an efficient unsupervised learning procedure, called Hybrid Protein Model (HPM), which is applied to the analysis of transmembrane proteins belonging to the all-α structural class. HPM method is an original classification procedure that efficiently combines sequence and structure learning. The procedure was initially applied to the analysis of globular proteins. In the present case, HPM classifies a set of overlapping protein fragments, extracted from a non-redundant databank of TMP 3D structure. After fine-tuning of the learning parameters, the optimal classification results in 65 clusters. They represent at best similar relationships between sequence and local structure properties of TMPs. Interestingly, HPM distinguishes among the resulting clusters two helical regions with distinct hydrophobic patterns. This underlines the complexity of the topology of these proteins. The HPM classification enlightens unusual relationship between amino acids in TMP fragments, which can be useful to elaborate new amino acids substitution matrices. Finally, two challenging applications are described: the first one aims at annotating protein functions (channel or not), the second one intends to assess the quality of the structures (X-ray or models) via a new scoring function deduced from the HPM classification.

Compound toxicity screening and structure-activity relationship modeling in Escherichia coli.

PubMed

Planson, Anne-Gaëlle; Carbonell, Pablo; Paillard, Elodie; Pollet, Nicolas; Faulon, Jean-Loup

2012-03-01

Synthetic biology and metabolic engineering are used to develop new strategies for producing valuable compounds ranging from therapeutics to biofuels in engineered microorganisms. When developing methods for high-titer production cells, toxicity is an important element to consider. Indeed the production rate can be limited due to toxic intermediates or accumulation of byproducts of the heterologous biosynthetic pathway of interest. Conversely, highly toxic molecules are desired when designing antimicrobials. Compound toxicity in bacteria plays a major role in metabolic engineering as well as in the development of new antibacterial agents. Here, we screened a diversified chemical library of 166 compounds for toxicity in Escherichia coli. The dataset was built using a clustering algorithm maximizing the chemical diversity in the library. The resulting assay data was used to develop a toxicity predictor that we used to assess the toxicity of metabolites throughout the metabolome. This new tool for predicting toxicity can thus be used for fine-tuning heterologous expression and can be integrated in a computational-framework for metabolic pathway design. Many structure-activity relationship tools have been developed for toxicology studies in eukaryotes [Valerio (2009), Toxicol Appl Pharmacol, 241(3): 356-370], however, to the best of our knowledge we present here the first E. coli toxicity prediction web server based on QSAR models (EcoliTox server: http://www.issb.genopole.fr/∼faulon/EcoliTox.php). Copyright © 2011 Wiley Periodicals, Inc.

40 CFR 132.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Species Act. Existing Great Lakes discharger is any building, structure, facility, or installation from... discharger is any building, structure, facility, or installation from which there is or may be a “discharge... monitoring of the contaminant. Quantitative structure activity relationship (QSAR) or structure activity...

Structure—activity relationships for insecticidal carbamates*

PubMed Central

Metcalf, Robert L.

1971-01-01

Carbamate insecticides are biologically active because of their structural complementarity to the active site of acetylcholinesterase (AChE) and their consequent action as substrates with very low turnover numbers. Carbamates behave as synthetic neurohormones that produce their toxic action by interrupting the normal action of AChE so that acetylcholine accumulates at synaptic junctions. The necessary properties for a suitable insecticidal carbamate are lipid solubility, suitable structural complementarity to AChE, and sufficient stability to multifunction-oxidase detoxification. The relationships between the structure and the activity of a large number of synthetic carbamates are analysed in detail, with particular attention to the second of these properties. PMID:5315358

The Moderating Effect of Health-Improving Workplace Environment on Promoting Physical Activity in White-Collar Employees: A Multi-Site Longitudinal Study Using Multi-Level Structural Equation Modeling.

PubMed

Watanabe, Kazuhiro; Otsuka, Yasumasa; Shimazu, Akihito; Kawakami, Norito

2016-02-01

This longitudinal study aimed to investigate the moderating effect of health-improving workplace environment on relationships between physical activity, self-efficacy, and psychological distress. Data were collected from 16 worksites and 129 employees at two time-points. Health-improving workplace environment was measured using the Japanese version of the Environmental Assessment Tool. Physical activity, self-efficacy, and psychological distress were also measured. Multi-level structural equation modeling was used to investigate the moderating effect of health-improving workplace environment on relationships between psychological distress, self-efficacy, and physical activity. Psychological distress was negatively associated with physical activity via low self-efficacy. Physical activity was negatively related to psychological distress. Physical activity/fitness facilities in the work environment exaggerated the positive relationship between self-efficacy and physical activity. Physical activity/fitness facilities in the workplace may promote employees' physical activity.

Pyramidal neurovision architecture for vision machines

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1993-08-01

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

Synthesis and Structure activity relationships of EGCG Analogues, A Recently Identified Hsp90 Inhibitor

PubMed Central

Khandelwal, Anuj; Hall, Jessica

2014-01-01

Epigallocatechin-3-gallate (EGCG), the principal polyphenol isolated from green tea, was recently shown to inhibit Hsp90, however structure-activity relationships for this natural product have not yet been produced. Herein, we report the synthesis and biological evaluation of EGCG analogues to establish structure-activity relationships between EGCG and Hsp90. All four rings as well as the linker connecting the C- and the D-rings were systematically investigated, which led to the discovery of compounds that inhibit Hs90 and display improvement in efficacy over EGCG. Anti-proliferative activity of all the analogues was determined against MCF-7 and SKBr3 cell lines and Hsp90 inhibitory activity of four most potent analogues was further evaluated by western blot analyses and degradation of Hsp90-dependent client proteins. Prenyl substituted aryl ester of 3,5-dihydroxychroman-3-ol ring system was identified as novel scaffold that exhibit Hsp90 inhibitory activity. PMID:23834230

Improving the Perceptual Performance of Learning Disabled Second Graders through Computer Assisted Instruction.

ERIC Educational Resources Information Center

Burke, James P.

The practicum designed a perceptual activities program for learning disabled second graders using computer-assisted instruction. The program develops skills involving visual motor coordination, figure-ground differentiation, form constancy, position in space, and spatial relationships. Five behavioral objectives for each developmental area were…

In silico genotoxicity of coumarins: application of the Phenol-Explorer food database to functional food science.

PubMed

Guardado Yordi, E; Matos, M J; Pérez Martínez, A; Tornes, A C; Santana, L; Molina, E; Uriarte, E

2017-08-01

Coumarins are a group of phytochemicals that may be beneficial or harmful to health depending on their type and dosage and the matrix that contains them. Some of these compounds have been proven to display pro-oxidant and clastogenic activities. Therefore, in the current work, we have studied the coumarins that are present in food sources extracted from the Phenol-Explorer database in order to predict their clastogenic activity and identify the structure-activity relationships and genotoxic structural alerts using alternative methods in the field of computational toxicology. It was necessary to compile information on the type and amount of coumarins in different food sources through the analysis of databases of food composition available online. A virtual screening using a clastogenic model and different software, such as MODESLAB, ChemDraw and STATISTIC, was performed. As a result, a table of food composition was prepared and qualitative information from this data was extracted. The virtual screening showed that the esterified substituents inactivate molecules, while the methoxyl and hydroxyl substituents contribute to their activity and constitute, together with the basic structures of the studied subclasses, clastogenic structural alerts. Chemical subclasses of simple coumarins and furocoumarins were classified as active (xanthotoxin, isopimpinellin, esculin, scopoletin, scopolin and bergapten). In silico genotoxicity was mainly predicted for coumarins found in beer, sherry, dried parsley, fresh parsley and raw celery stalks. The results obtained can be interesting for the future design of functional foods and dietary supplements. These studies constitute a reference for the genotoxic chemoinformatic analysis of bioactive compounds present in databases of food composition.

Evaluation and structure-activity relationship analysis of a new series of 4-imino-5H-pyrazolo[3,4-d]pyrimidin-5-amines as potential antibacterial agents

NASA Astrophysics Data System (ADS)

Beyzaei, Hamid; Aryan, Reza; Moghaddam-Manesh, Mohammadreza; Ghasemi, Behzad; Karimi, Pouya; Samareh Delarami, Hojat; Sanchooli, Mahmood

2017-09-01

The synthesis of pyrazolo[3,4-d]pyrimidine derivatives is important due to their presence in various biologically active compounds such as anticancer, antimicrobial, antiparasitic, anti-inflammatory and antidiabetic agents. In this project, a new and efficient approach for the synthesis of some novel 4-imino-5H-pyrazolo[3,4-d]pyrimidin-5-amines from reaction of 5-amino-pyrazole-4-carbonitrile with various hydrazides in ethanolic sodium ethoxide medium was reported. Antimicrobial activities of all synthesized derivatives were evaluated against eight Gram-positive and five Gram-negative pathogenic bacteria. The moderate to good inhibitory effects were observed based on inhibition zone diameter (IZD), minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values. In order to determine the reasonable relationship between antibacterial activities and physiochemical properties of the derivatives, computational studies were carried out in terms of geometry optimization, short-range van der Waals forces, dipole moments, atomic charges and frontier orbital energies. It was found that both short-range forces and covalent bonds are important in the observed inhibitory effects of the molecules. The results suggested that pyrazolo[3,4-d]pyrimidine derivatives prefer a soft nucleophilic attack on bio-macromolecular targets. Furthermore, our models proposed that the antibacterial activities of these derivatives can be improved by substituting large electron donating groups on the 6-phenyl rings.

Experimental and Computational Analysis of Polyglutamine-Mediated Cytotoxicity

PubMed Central

Tang, Matthew Y.; Proctor, Carole J.; Woulfe, John; Gray, Douglas A.

2010-01-01

Expanded polyglutamine (polyQ) proteins are known to be the causative agents of a number of human neurodegenerative diseases but the molecular basis of their cytoxicity is still poorly understood. PolyQ tracts may impede the activity of the proteasome, and evidence from single cell imaging suggests that the sequestration of polyQ into inclusion bodies can reduce the proteasomal burden and promote cell survival, at least in the short term. The presence of misfolded protein also leads to activation of stress kinases such as p38MAPK, which can be cytotoxic. The relationships of these systems are not well understood. We have used fluorescent reporter systems imaged in living cells, and stochastic computer modeling to explore the relationships of polyQ, p38MAPK activation, generation of reactive oxygen species (ROS), proteasome inhibition, and inclusion body formation. In cells expressing a polyQ protein inclusion, body formation was preceded by proteasome inhibition but cytotoxicity was greatly reduced by administration of a p38MAPK inhibitor. Computer simulations suggested that without the generation of ROS, the proteasome inhibition and activation of p38MAPK would have significantly reduced toxicity. Our data suggest a vicious cycle of stress kinase activation and proteasome inhibition that is ultimately lethal to cells. There was close agreement between experimental data and the predictions of a stochastic computer model, supporting a central role for proteasome inhibition and p38MAPK activation in inclusion body formation and ROS-mediated cell death. PMID:20885783

Computational medicinal chemistry in fragment-based drug discovery: what, how and when.

PubMed

Rabal, Obdulia; Urbano-Cuadrado, Manuel; Oyarzabal, Julen

2011-01-01

The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure-activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario - what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.

Casein Hydrolysates by Lactobacillus brevis and Lactococcus lactis Proteases: Peptide Profile Discriminates Strain-Dependent Enzyme Specificity.

PubMed

Bounouala, Fatima Zohra; Roudj, Salima; Karam, Nour-Eddine; Recio, Isidra; Miralles, Beatriz

2017-10-25

Casein from ovine and bovine milk were hydrolyzed with two extracellular protease preparations from Lactobacillus brevis and Lactococcus lactis. The hydrolysates were analyzed by HPLC-MS/MS for peptide identification. A strain-dependent peptide profile could be observed, regardless of the casein origin, and the specificity of these two proteases could be computationally ascribed. The cleavage pattern yielding phenylalanine, leucine, or tyrosine at C-terminal appeared both at L. lactis and Lb. brevis hydrolysates. However, the cleavage C-terminal to lysine was favored with Lb. brevis protease. The hydrolysates showed ACE-inhibitory activity with IC 50 in the 16-70 μg/mL range. Ovine casein hydrolysates yielded greater ACE-inhibitory activity. Previously described antihypertensive and opioid peptides were found in these ovine and bovine casein hydrolysates and prediction of the antihypertensive activity of the sequences based on quantitative structure and activity relationship (QSAR) was performed. This approach might represent a useful classification tool regarding health-related properties prior to further purification.

Structure-anti-MRSA activity relationship of macrocyclic bis(bibenzyl) derivatives.

PubMed

Sawada, Hiromi; Onoda, Kenji; Morita, Daichi; Ishitsubo, Erika; Matsuno, Kenji; Tokiwa, Hiroaki; Kuroda, Teruo; Miyachi, Hiroyuki

2013-12-15

We synthesized a series of macrocyclic bis(bibenzyl) derivatives, including riccardin-, isoplagiochin- and marchantin-class structures, and evaluated their antibacterial activity towards methicillin-resistant Staphylococcus aureus (anti-MRSA activity). The structure-activity relationships and the results of molecular dynamics simulations indicated that bis(bibenzyl)s with potent anti-MRSA activity commonly have a 4-hydroxyl group at the D-benzene ring and a 2-hydroxyl group at the C-benzene ring in the hydrophilic part of the molecule, and an unsubstituted phenoxyphenyl group in the hydrophobic part of the molecule containing the A-B-benzene rings. Pharmacological characterization of the bis(bibenzyl) derivatives and 2-phenoxyphenol fragment 25, previously proposed as the minimum structure of riccardin C 1 for anti-MRSA activity, indicated that they have different action mechanisms: the bis(bibenzyl)s are bactericidal, while 25 is bacteriostatic, showing only weak bactericidal activity. Copyright © 2013 Elsevier Ltd. All rights reserved.

TOWARDS REFINED USE OF TOXICITY DATA IN ...

EPA Pesticide Factsheets

In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants. In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants.

Structure-activity relationships of rationally designed AMACR 1A inhibitors.

PubMed

Yevglevskis, Maksims; Lee, Guat L; Nathubhai, Amit; Petrova, Yoana D; James, Tony D; Threadgill, Michael D; Woodman, Timothy J; Lloyd, Matthew D

2018-04-30

α-Methylacyl-CoA racemase (AMACR; P504S) is a promising novel drug target for prostate and other cancers. Assaying enzyme activity is difficult due to the reversibility of the 'racemisation' reaction and the difficulties in the separation of epimeric products; consequently few inhibitors have been described and no structure-activity relationship study has been performed. This paper describes the first structure-activity relationship study, in which a series of 23 known and potential rational AMACR inhibitors were evaluated. AMACR was potently inhibited (IC 50  = 400-750 nM) by ibuprofenoyl-CoA and derivatives. Potency was positively correlated with inhibitor lipophilicity. AMACR was also inhibited by straight-chain and branched-chain acyl-CoA esters, with potency positively correlating with inhibitor lipophilicity. 2-Methyldecanoyl-CoAs were ca. 3-fold more potent inhibitors than decanoyl-CoA, demonstrating the importance of the 2-methyl group for effective inhibition. Elimination substrates and compounds with modified acyl-CoA cores were also investigated, and shown to be potent inhibitors. These results are the first to demonstrate structure-activity relationships of rational AMACR inhibitors and that potency can be predicted by acyl-CoA lipophilicity. The study also demonstrates the utility of the colorimetric assay for thorough inhibitor characterisation. Copyright © 2018 Elsevier Inc. All rights reserved.

The Relationship between Cyber-Loafing and Internet Addiction

ERIC Educational Resources Information Center

Keser, Hafize; Kavuk, Melike; Numanoglu, Gulcan

2016-01-01

The goal of this study was to investigate the relationship between preservice teachers' internet addiction level and cyber-loafing activities. This study was conducted as a survey study. Participants of the study was Computer Education and Instructional Technology department students (n = 139) at Ankara University. "Cyber loafing activity…

Quantum chemical and experimental studies on the structure and vibrational spectra of an alkaloid-Corlumine

NASA Astrophysics Data System (ADS)

Mishra, Rashmi; Joshi, Bhawani Datt; Srivastava, Anubha; Tandon, Poonam; Jain, Sudha

2014-01-01

The study concentrates on an important natural product, phthalide isoquinoline alkaloid Corlumine (COR) [(6R)-6-[(1S)-1,2,3,4-Tetrahydro-6,7-dimethoxy-2-methylisoquinolin-1-yl] furo [3,4-e]-1,3-benzodioxol-8(6H)-one] well known to exhibit spasmolytic and GABA antagonist activity. It was fully characterized by a variety of experimental methods including vibrational spectroscopy (IR and Raman), thermal analysis (DSC), UV and SEM. For a better interpretation and analysis of the results quantum chemical calculations employing DFT were also performed. TD-DFT was employed to elucidate electronic properties for both gaseous and solvent environment using IEF-PCM model. Graphical representation of HOMO and LUMO would provide a valuable insight into the nature of reactivity and some of the structural and physical properties of the title molecule. The structure-activity relationship have been interpreted by mapping electrostatic potential surface (MEP), which is valuable information for the quality control of medicines and drug-receptor interactions. Stability of the molecule arising from hyper conjugative interactions, charge delocalisation has been analyzed using natural bond orbital (NBO) analysis. Computation of thermodynamical properties would help to have a deep insight into the molecule for further applications.

Anti-infectious drug repurposing using an integrated chemical genomics and structural systems biology approach.

PubMed

Ng, Clara; Hauptman, Ruth; Zhang, Yinliang; Bourne, Philip E; Xie, Lei

2014-01-01

The emergence of multi-drug and extensive drug resistance of microbes to antibiotics poses a great threat to human health. Although drug repurposing is a promising solution for accelerating the drug development process, its application to anti-infectious drug discovery is limited by the scope of existing phenotype-, ligand-, or target-based methods. In this paper we introduce a new computational strategy to determine the genome-wide molecular targets of bioactive compounds in both human and bacterial genomes. Our method is based on the use of a novel algorithm, ligand Enrichment of Network Topological Similarity (ligENTS), to map the chemical universe to its global pharmacological space. ligENTS outperforms the state-of-the-art algorithms in identifying novel drug-target relationships. Furthermore, we integrate ligENTS with our structural systems biology platform to identify drug repurposing opportunities via target similarity profiling. Using this integrated strategy, we have identified novel P. falciparum targets of drug-like active compounds from the Malaria Box, and suggest that a number of approved drugs may be active against malaria. This study demonstrates the potential of an integrative chemical genomics and structural systems biology approach to drug repurposing.

Structure-Activity Relationships for in vitro Diuretic Activity of CAP2b in the Housefly

DTIC Science & Technology

2007-01-01

p e p t i d e s 2 8 ( 2 0 0 7 ) 5 7 – 6 1Structure-activity relationships for in vitro diuretic activity of CAP2b in the housefly Ronald J. Nachman a...the peptide Manse-CAP2b (pELYAFPRV-NH2) were assayed for diuretic activity on Malpighian tubules of the housefly Musca domestica (M. domestica). The C...required the C-terminal heptapeptide, which was equipotent with the most active of the native housefly CAP2b peptides. Replacement of Arg7 and Val8 with

Computer-aided discovery of a metal-organic framework with superior oxygen uptake.

PubMed

Moghadam, Peyman Z; Islamoglu, Timur; Goswami, Subhadip; Exley, Jason; Fantham, Marcus; Kaminski, Clemens F; Snurr, Randall Q; Farha, Omar K; Fairen-Jimenez, David

2018-04-11

Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge.

Advantages and limitations of classic and 3D QSAR approaches in nano-QSAR studies based on biological activity of fullerene derivatives

DOE PAGES

Jagiello, Karolina; Grzonkowska, Monika; Swirog, Marta; ...

2016-08-29

In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure–Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure–Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Comparative Molecular Similarity Indices Analysis, CoMSIA analysis employed for nanomaterials) have been briefly summarized. Both approaches were compared according to the selected criteria, including: efficiency, type of experimental data, class of nanomaterials, time required for calculations and computational cost, difficulties in the interpretation. Taking into account the advantages and limitations of each method, we provide themore » recommendations for nano-QSAR modellers and QSAR model users to be able to determine a proper and efficient methodology to investigate biological activity of nanoparticles in order to describe the underlying interactions in the most reliable and useful manner.« less

Advantages and limitations of classic and 3D QSAR approaches in nano-QSAR studies based on biological activity of fullerene derivatives

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

Jagiello, Karolina; Grzonkowska, Monika; Swirog, Marta

In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure–Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure–Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Comparative Molecular Similarity Indices Analysis, CoMSIA analysis employed for nanomaterials) have been briefly summarized. Both approaches were compared according to the selected criteria, including: efficiency, type of experimental data, class of nanomaterials, time required for calculations and computational cost, difficulties in the interpretation. Taking into account the advantages and limitations of each method, we provide themore » recommendations for nano-QSAR modellers and QSAR model users to be able to determine a proper and efficient methodology to investigate biological activity of nanoparticles in order to describe the underlying interactions in the most reliable and useful manner.« less

Phylogenetic profiles reveal structural/functional determinants of TRPC3 signal-sensing antennae

PubMed Central

Ko, Kyung Dae; Bhardwaj, Gaurav; Hong, Yoojin; Chang, Gue Su; Kiselyov, Kirill

2009-01-01

Biochemical assessment of channel structure/function is incredibly challenging. Developing computational tools that provide these data would enable translational research, accelerating mechanistic experimentation for the bench scientist studying ion channels. Starting with the premise that protein sequence encodes information about structure, function and evolution (SF&E), we developed a unified framework for inferring SF&E from sequence information using a knowledge-based approach. The Gestalt Domain Detection Algorithm-Basic Local Alignment Tool (GDDA-BLAST) provides phylogenetic profiles that can model, ab initio, SF&E relationships of biological sequences at the whole protein, single domain and single-amino acid level.1,2 In our recent paper,4 we have applied GDDA-BLAST analysis to study canonical TRP (TRPC) channels1 and empirically validated predicted lipid-binding and trafficking activities contained within the TRPC3 TRP_2 domain of unknown function. Overall, our in silico, in vitro, and in vivo experiments support a model in which TRPC3 has signal-sensing antennae which are adorned with lipid-binding, trafficking and calmodulin regulatory domains. In this Addendum, we correlate our functional domain analysis with the cryo-EM structure of TRPC3.3 In addition, we synthesize recent studies with our new findings to provide a refined model on the mechanism(s) of TRPC3 activation/deactivation. PMID:19704910

Structure-Activity Relationships of 33 Piperidines as Toxicants Against Female Adults of Aedes aegypti (Diptera: Culicidae)

DTIC Science & Technology

2007-03-01

alkaloid piperine and 12 syn- thetic derivatives have been evaluated against epimas- tigote and amastigote forms of the protozoan parasite Trypanosoma...O. Kris- tiansen, P. Maienfisch, A. Pascual, and A. Rindlisbacher. 2001. Synthesis and structure-activity relationships of benzophenone hydrazone...Am. J. Trop. Med. Hyg. 22: 124Ð 129. Creemer, L. C., H. A. Kirst, J.W. Paschal, and T. V.Worden. 2000. Synthesis and insecticidal activity of spinosyn

GirlPOWER! Strengthening Mentoring Relationships through a Structured, Gender-Specific Program

ERIC Educational Resources Information Center

Pryce, Julia M.; Silverthorn, Naida; Sanchez, Bernadette; DuBois, David L.

2010-01-01

The authors examine GirlPOWER! an innovative program that uses structure and group-based activities to enhance one-to-one mentoring relationships for young adolescent girls from the perspective of the focus, purpose, and authorship dimensions of mentoring relationships that Karcher and Nakkula described. The discussion draws on several sources of…

Structural optimization of N1-aryl-benzimidazoles for the discovery of new non-nucleoside reverse transcriptase inhibitors active against wild-type and mutant HIV-1 strains.

PubMed

Monforte, Anna Maria; De Luca, Laura; Buemi, Maria Rosa; Agharbaoui, Fatima E; Pannecouque, Christophe; Ferro, Stefania

2018-02-01

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are recommended components of preferred combination antiretroviral therapies used for the treatment of human immunodeficiency virus (HIV) infection. These regimens are extremely effective in suppressing virus replication. Recently, our research group identified some N 1 -aryl-2-arylthioacetamido-benzimidazoles as a novel class of NNRTIs. In this research work we report the design, the synthesis and the structure-activity relationship studies of new compounds (20-34) in which some structural modifications have been introduced in order to investigate their effects on reverse transcriptase (RT) inhibition and to better define the features needed to increase the antiviral activity. Most of the new compounds proved to be highly effective in inhibiting both RT enzyme at nanomolar concentrations and HIV-1 replication in MT4 cells with minimal cytotoxicity. Among them, the most promising N 1 -aryl-2-arylthioacetamido-benzimidazoles and N 1 -aryl-2-aryloxyacetamido-benzimidazoles were also tested toward a panel of single- and double-mutants strain responsible for resistance to NNRTIs, showing in vitro antiviral activity toward single mutants L100I, K103N, Y181C, Y188L and E138K. The best results were observed for derivatives 29 and 33 active also against the double mutants F227L and V106A. Computational approaches were applied in order to rationalize the potency of the new synthesized inhibitors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inelastic behavior of structural components

NASA Technical Reports Server (NTRS)

Hussain, N.; Khozeimeh, K.; Toridis, T. G.

1980-01-01

A more accurate procedure was developed for the determination of the inelastic behavior of structural components. The actual stress-strain curve for the mathematical of the structure was utilized to generate the force-deformation relationships for the structural elements, rather than using simplified models such as elastic-plastic, bilinear and trilinear approximations. relationships were generated for beam elements with various types of cross sections. In the generational of these curves, stress or load reversals, kinematic hardening and hysteretic behavior were taken into account. Intersections between loading and unloading branches were determined through an iterative process. Using the inelastic properties obtained, the plastic static response of some simple structural systems composed of beam elements was computed. Results were compared with known solutions, indicating a considerable improvement over response predictions obtained by means of simplified approximations used in previous investigations.

System and method for generating and/or screening potential metal-organic frameworks

DOEpatents

Wilmer, Christopher E; Leaf, Michael; Snurr, Randall Q; Farha, Omar K; Hupp, Joseph T

2015-04-21

A system and method for systematically generating potential metal-organic framework (MOFs) structures given an input library of building blocks is provided herein. One or more material properties of the potential MOFs are evaluated using computational simulations. A range of material properties (surface area, pore volume, pore size distribution, powder x-ray diffraction pattern, methane adsorption capability, and the like) can be estimated, and in doing so, illuminate unidentified structure-property relationships that may only have been recognized by taking a global view of MOF structures. In addition to identifying structure-property relationships, this systematic approach to identify the MOFs of interest is used to identify one or more MOFs that may be useful for high pressure methane storage.

System and method for generating and/or screening potential metal-organic frameworks

DOEpatents

Wilmer, Christopher E; Leaf, Michael; Snurr, Randall Q; Farha, Omar K; Hupp, Joseph T

2014-12-02

A system and method for systematically generating potential metal-organic framework (MOFs) structures given an input library of building blocks is provided herein. One or more material properties of the potential MOFs are evaluated using computational simulations. A range of material properties (surface area, pore volume, pore size distribution, powder x-ray diffraction pattern, methane adsorption capability, and the like) can be estimated, and in doing so, illuminate unidentified structure-property relationships that may only have been recognized by taking a global view of MOF structures. In addition to identifying structure-property relationships, this systematic approach to identify the MOFs of interest is used to identify one or more MOFs that may be useful for high pressure methane storage.

Computational predictions of zinc oxide hollow structures

NASA Astrophysics Data System (ADS)

Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

2018-03-01

Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

Redox properties of structural Fe in clay minerals: 3. Relationships between smectite redox and structural properties.

PubMed

Gorski, Christopher A; Klüpfel, Laura E; Voegelin, Andreas; Sander, Michael; Hofstetter, Thomas B

2013-01-01

Structural Fe in clay minerals is an important redox-active species in many pristine and contaminated environments as well as in engineered systems. Understanding the extent and kinetics of redox reactions involving Fe-bearing clay minerals has been challenging due to the inability to relate structural Fe(2+)/Fe(total) fractions to fundamental redox properties, such as reduction potentials (EH). Here, we overcame this challenge by using mediated electrochemical reduction (MER) and oxidation (MEO) to characterize the fraction of redox-active structural Fe (Fe(2+)/Fe(total)) in smectites over a wide range of applied EH-values (-0.6 V to +0.6 V). We examined Fe(2+)/Fe(total )- EH relationships of four natural Fe-bearing smectites (SWy-2, SWa-1, NAu-1, NAu-2) in their native, reduced, and reoxidized states and compared our measurements with spectroscopic observations and a suite of mineralogical properties. All smectites exhibited unique Fe(2+)/Fe(total) - EH relationships, were redox active over wide EH ranges, and underwent irreversible electron transfer induced structural changes that were observable with X-ray absorption spectroscopy. Variations among the smectite Fe(2+)/Fe(total) - EH relationships correlated well with both bulk and molecular-scale properties, including Fe(total) content, layer charge, and quadrupole splitting values, suggesting that multiple structural parameters determined the redox properties of smectites. The Fe(2+)/Fe(total) - EH relationships developed for these four commonly studied clay minerals may be applied to future studies interested in relating the extent of structural Fe reduction or oxidation to EH-values.

Transforming Benzophenoxazine Laser Dyes into Chromophores for Dye-Sensitized Solar Cells: A Molecular Engineering Approach

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

Schröder, Florian A. Y. N.; Cole, Jacqueline M.; Waddell, Paul G.

2015-02-03

The re-functionalization of a series of four well-known industrial laser dyes, based on benzophenoxazine, is explored with the prospect of molecularly engineering new chromophores for dye-sensitized solar cell (DSC) applications. Such engineering is important since a lack of suitable dyes is stifling the progress of DSC technology. The conceptual idea involves making laser dyes DSC-active by chemical modification, while maintaining their key property attributes that are attractive to DSC applications. This molecular engineering follows a step-wise approach. Firstly, molecular structures and optical absorption properties are determined for the parent laser dyes: Cresyl Violet (1); Oxazine 170 (2); Nile Blue Amore » (3), Oxazine 750 (4). These reveal structure-property relationships which define the prerequisites for computational molecular design of DSC dyes; the nature of their molecular architecture (D-π-A) and intramolecular charge transfer. Secondly, new DSC dyes are computationally designed by the in silico addition of a carboxylic acid anchor at various chemical substitution points in the parent laser dyes. A comparison of the resulting frontier molecular orbital energy levels with the conduction band edge of a TiO2 DSC photoanode and the redox potential of two electrolyte options I-/I3- and Co(II/III)tris(bipyridyl) suggests promise for these computationally designed dyes as co-sensitizers for DSC applications.« less

Computer work and self-reported variables on anthropometrics, computer usage, work ability, productivity, pain, and physical activity

PubMed Central

2013-01-01

Background Computer users often report musculoskeletal complaints and pain in the upper extremities and the neck-shoulder region. However, recent epidemiological studies do not report a relationship between the extent of computer use and work-related musculoskeletal disorders (WMSD). The aim of this study was to conduct an explorative analysis on short and long-term pain complaints and work-related variables in a cohort of Danish computer users. Methods A structured web-based questionnaire including questions related to musculoskeletal pain, anthropometrics, work-related variables, work ability, productivity, health-related parameters, lifestyle variables as well as physical activity during leisure time was designed. Six hundred and ninety office workers completed the questionnaire responding to an announcement posted in a union magazine. The questionnaire outcomes, i.e., pain intensity, duration and locations as well as anthropometrics, work-related variables, work ability, productivity, and level of physical activity, were stratified by gender and correlations were obtained. Results Women reported higher pain intensity, longer pain duration as well as more locations with pain than men (P < 0.05). In parallel, women scored poorer work ability and ability to fulfil the requirements on productivity than men (P < 0.05). Strong positive correlations were found between pain intensity and pain duration for the forearm, elbow, neck and shoulder (P < 0.001). Moderate negative correlations were seen between pain intensity and work ability/productivity (P < 0.001). Conclusions The present results provide new key information on pain characteristics in office workers. The differences in pain characteristics, i.e., higher intensity, longer duration and more pain locations as well as poorer work ability reported by women workers relate to their higher risk of contracting WMSD. Overall, this investigation confirmed the complex interplay between anthropometrics, work ability, productivity, and pain perception among computer users. PMID:23915209

Learning and cognitive styles in web-based learning: theory, evidence, and application.

PubMed

Cook, David A

2005-03-01

Cognitive and learning styles (CLS) have long been investigated as a basis to adapt instruction and enhance learning. Web-based learning (WBL) can reach large, heterogenous audiences, and adaptation to CLS may increase its effectiveness. Adaptation is only useful if some learners (with a defined trait) do better with one method and other learners (with a complementary trait) do better with another method (aptitude-treatment interaction). A comprehensive search of health professions education literature found 12 articles on CLS in computer-assisted learning and WBL. Because so few reports were found, research from non-medical education was also included. Among all the reports, four CLS predominated. Each CLS construct was used to predict relationships between CLS and WBL. Evidence was then reviewed to support or refute these predictions. The wholist-analytic construct shows consistent aptitude-treatment interactions consonant with predictions (wholists need structure, a broad-before-deep approach, and social interaction, while analytics need less structure and a deep-before-broad approach). Limited evidence for the active-reflective construct suggests aptitude-treatment interaction, with active learners doing better with interactive learning and reflective learners doing better with methods to promote reflection. As predicted, no consistent interaction between the concrete-abstract construct and computer format was found, but one study suggests that there is interaction with instructional method. Contrary to predictions, no interaction was found for the verbal-imager construct. Teachers developing WBL activities should consider assessing and adapting to accommodate learners defined by the wholist-analytic and active-reflective constructs. Other adaptations should be considered experimental. Further WBL research could clarify the feasibility and effectiveness of assessing and adapting to CLS.

Density functional theory in materials science.

PubMed

Neugebauer, Jörg; Hickel, Tilmann

2013-09-01

Materials science is a highly interdisciplinary field. It is devoted to the understanding of the relationship between (a) fundamental physical and chemical properties governing processes at the atomistic scale with (b) typically macroscopic properties required of materials in engineering applications. For many materials, this relationship is not only determined by chemical composition, but strongly governed by microstructure. The latter is a consequence of carefully selected process conditions (e.g., mechanical forming and annealing in metallurgy or epitaxial growth in semiconductor technology). A key task of computational materials science is to unravel the often hidden composition-structure-property relationships using computational techniques. The present paper does not aim to give a complete review of all aspects of materials science. Rather, we will present the key concepts underlying the computation of selected material properties and discuss the major classes of materials to which they are applied. Specifically, our focus will be on methods used to describe single or polycrystalline bulk materials of semiconductor, metal or ceramic form.

PLS-based quantitative structure-activity relationship for substituted benzamides of clebopride type. Application of experimental design in drug design.

PubMed

Norinder, U; Högberg, T

1992-04-01

The advantageous approach of using an experimentally designed training set as the basis for establishing a quantitative structure-activity relationship with good predictive capability is described. The training set was selected from a fractional factorial design scheme based on a principal component description of physico-chemical parameters of aromatic substituents. The derived model successfully predicts the activities of additional substituted benzamides of 6-methoxy-N-(4-piperidyl)salicylamide type. The major influence on activity of the 3-substituent is demonstrated.

Structure-activity relationships of tetramethylpiperidine-substituted phenazines against Mycobacterium leprae in vitro.

PubMed Central

Franzblau, S G; White, K E; O'Sullivan, J F

1989-01-01

In a previous study of structure-activity relationships of selected phenazines against Mycobacterium leprae in vitro, compounds containing a 2,2,6,6-tetramethylpiperidine substitution at the imino nitrogen were most active. Therefore, the effect of substitution at the para positions of the phenyl and anilino groups in tetramethylpiperidine-substituted phenazines was assessed. As determined by radiorespirometry, activity in ascending order was observed in compounds substituted with hydrogens or fluorines, ethoxy groups, methyl groups, chlorines, and bromines and correlated with partition coefficients in octanol-water. PMID:2692516

Discovery of imidazo[1,2-b]pyridazine derivatives as IKKbeta inhibitors. Part 1: Hit-to-lead study and structure-activity relationship.

PubMed

Shimizu, Hiroki; Tanaka, Shinji; Toki, Tadashi; Yasumatsu, Isao; Akimoto, Toshihiko; Morishita, Kaoru; Yamasaki, Tomonori; Yasukochi, Takanori; Iimura, Shin

2010-09-01

Imidazo[1,2-b]pyridazine derivatives from high-throughput screening were developed as IKKbeta inhibitors. By the optimization of the 3- and 6-position of imidazo[1,2-b]pyridazine scaffold, cell-free IKKbeta inhibitory activity and TNFalpha inhibitory activity in THP-1 cell increased. Also, these compounds showed high kinase selectivity. The structure-activity relationship was revealed and the interaction model of imidazo[1,2-b]pyridazine compounds with IKKbeta was constructed. Copyright 2010. Published by Elsevier Ltd.

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

3-cyanoindole-based inhibitors of inosine monophosphate dehydrogenase: synthesis and initial structure-activity relationships.

PubMed

Dhar, T G Murali; Shen, Zhongqi; Gu, Henry H; Chen, Ping; Norris, Derek; Watterson, Scott H; Ballentine, Shelley K; Fleener, Catherine A; Rouleau, Katherine A; Barrish, Joel C; Townsend, Robert; Hollenbaugh, Diane L; Iwanowicz, Edwin J

2003-10-20

A series of novel small molecule inhibitors of inosine monophosphate dehydrogenase (IMPDH), based upon a 3-cyanoindole core, were explored. IMPDH catalyzes the rate determining step in guanine nucleotide biosynthesis and is a target for anticancer, immunosuppressive and antiviral therapy. The synthesis and the structure-activity relationships (SAR), derived from in vitro studies, for this new series of inhibitors is given.

Notes on quantitative structure-properties relationships (QSPR) (1): A discussion on a QSPR dimensionality paradox (QSPR DP) and its quantum resolution.

PubMed

Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J

2009-05-01

Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.

Studies of structure-activity relationship on plant polyphenol-induced suppression of human liver cancer cells.

PubMed

Loa, Jacky; Chow, Pierce; Zhang, Kai

2009-05-01

To study anticancer activities of 68 plant polyphenols with different backbone structures and various substitutions and to analyze the structure-activity relationships. Antiproliferative activity of 68 plant polyphenols on human liver cancer cells were screened by the 3-[4,5-dimethylthiazol-2yl]-2,5-diphenyltetrazolium bromide method. Structure-activity relationships were analyzed by comparison of their activities with selected structures. Cell cycle progression was assayed by flow cytometry analysis and apoptosis was analyzed by DNA fragment assay. Based on their backbone structures, 68 polyphenols were sub-classed to flavonoids (chalcones, flavanones, flavones and isoflavones), chromones and coumarins. The order of their potency to suppress the human liver cancer cells is chalcones > flavones > chromones > isoflavones > flavanones > coumarins. Chalcones comprise the most potent group with IC(50) values ranging from 21.69 to 197 microM. Top nine most potent chalcones in the group have hydroxylation at 2'-carbon position in B-ring. Flavones ranked second in their potencies. Quercetin, 4-hydroxyflavone and luteolin are three hydroxyflavones with highest potencies in this group. Their IC(50) values are 30.81, 39.29 and 71.17 microM, respectively. Chromones, isoflavones, flavanones and coumarins showed much lower potencies when compared to the first two groups with IC(50) ranges of 61 to >400, 131 to >400, 138 to >400 and 360.85 to >400 microM, respectively. In mechanistic studies, the most potent chalcone, 2,2'-dihydroxychalcone could induce G2/M arrest and then apoptosis of the cancer cells. An analysis of structure-activity relationship showed that following structures are required for their inhibitory potencies on human liver cancer cells: (1) of the six sub-classes of the polyphenols tested, the unique backbone structure of chalcones with a open C-ring; (2) within the chalcone group, hydroxyl substitution at 2'-carbon of B-ring; (3) hydroxyl substitution at 3'-carbon in B-ring of flavones. However, some other structures were found to decrease their potencies: e.g. substitutions by sugar moieties in flavones. These data are valuable for design and modification of new polyphenols, which could be potential antiproliferative agents of cancer cells.

Structure-activity relationship and docking studies of thiazolidinedione-type compounds with monoamine oxidase B.

PubMed

Carroll, Richard T; Dluzen, Dean E; Stinnett, Hilary; Awale, Prabha S; Funk, Max O; Geldenhuys, Werner J

2011-08-15

The neuroprotective activity of pioglitazone and rosiglitazone in the MPTP parkinsonian mouse prompted us to evaluate a set of thiazolidinedione (TZD) type compounds for monoamine oxidase A and B inhibition activity. These compounds were able to inhibit MAO-B over several log units of magnitude (82 nM to 600 μM). Initial structure-activity relationship studies identified key areas to modify the aromatic substituted TZD compounds. Primarily, substitutions on the aromatic group and the TZD nitrogen were key areas where activity was enhanced within this group of compounds. Copyright © 2011 Elsevier Ltd. All rights reserved.

Design and synthesis of emodin derivatives as novel inhibitors of ATP-citrate lyase.

PubMed

Koerner, Steffi K; Hanai, Jun-Ichi; Bai, Sha; Jernigan, Finith E; Oki, Miwa; Komaba, Chieko; Shuto, Emi; Sukhatme, Vikas P; Sun, Lijun

2017-01-27

Aberrant cellular metabolism drives cancer proliferation and metastasis. ATP citrate lyase (ACL) plays a critical role in generating cytosolic acetyl CoA, a key building block for de novo fatty acid and cholesterol biosynthesis. ACL is overexpressed in cancer cells, and siRNA knockdown of ACL limits cancer cell proliferation and reduces cancer stemness. We characterized a new class of ACL inhibitors bearing the key structural feature of the natural product emodin. Structure-activity relationship (SAR) study led to the identification of 1d as a potent lead that demonstrated dose-dependent inhibition of proliferation and cancer stemness of the A549 lung cancer cell line. Computational modeling indicates this class of inhibitors occupies an allosteric binding site and blocks the entrance of the substrate citrate to its binding site. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The HSP90 binding mode of a radicicol-like E-oxime from docking, binding free energy estimations, and NMR 15N chemical shifts

PubMed Central

Spichty, Martin; Taly, Antoine; Hagn, Franz; Kessler, Horst; Barluenga, Sofia; Winssinger, Nicolas; Karplus, Martin

2009-01-01

We determine the binding mode of a macrocyclic radicicol-like oxime to yeast HSP90 by combining computer simulations and experimental measurements. We sample the macrocyclic scaffold of the unbound ligand by parallel tempering simulations and dock the most populated conformations to yeast HSP90. Docking poses are then evaluated by the use of binding free energy estimations with the linear interaction energy method. Comparison of QM/MM-calculated NMR chemical shifts with experimental shift data for a selective subset of back-bone 15N provides an additional evaluation criteria. As a last test we check the binding modes against available structure-activity-relationships. We find that the most likely binding mode of the oxime to yeast HSP90 is very similar to the known structure of the radicicol-HSP90 complex. PMID:19482409

Ontology of fractures

NASA Astrophysics Data System (ADS)

Zhong, Jian; Aydina, Atilla; McGuinness, Deborah L.

2009-03-01

Fractures are fundamental structures in the Earth's crust and they can impact many societal and industrial activities including oil and gas exploration and production, aquifer management, CO 2 sequestration, waste isolation, the stabilization of engineering structures, and assessing natural hazards (earthquakes, volcanoes, and landslides). Therefore, an ontology which organizes the concepts of fractures could help facilitate a sound education within, and communication among, the highly diverse professional and academic community interested in the problems cited above. We developed a process-based ontology that makes explicit specifications about fractures, their properties, and the deformation mechanisms which lead to their formation and evolution. Our ontology emphasizes the relationships among concepts such as the factors that influence the mechanism(s) responsible for the formation and evolution of specific fracture types. Our ontology is a valuable resource with a potential to applications in a number of fields utilizing recent advances in Information Technology, specifically for digital data and information in computers, grids, and Web services.

In silico pharmacology for drug discovery: applications to targets and beyond

PubMed Central

Ekins, S; Mestres, J; Testa, B

2007-01-01

Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets. PMID:17549046

Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening.

PubMed

Castillo-Garit, Juan Alberto; del Toro-Cortés, Oremia; Vega, Maria C; Rolón, Miriam; Rojas de Arias, Antonieta; Casañola-Martin, Gerardo M; Escario, José A; Gómez-Barrio, Alicia; Marrero-Ponce, Yovani; Torrens, Francisco; Abad, Concepción

2015-01-01

Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a good agreement between theoretical predictions and experimental results. Three compounds showed IC50 values for epimastigote elimination (AE) lower than 50 μM, while for the benznidazole the IC50 = 54.7 μM which was used as reference compound. The value of IC50 for cytotoxicity of these compounds is at least 5 times greater than their value of IC50 for AE. Finally, we can say that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new antitrypanosomal compounds. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Structure-activity relationship of prenyl-substituted polyphenols from Artocarpus heterophyllus as inhibitors of melanin biosynthesis in cultured melanoma cells.

PubMed

Arung, Enos Tangke; Shimizu, Kuniyoshi; Kondo, Ryuichiro

2007-09-01

A series of prenylated, flavone-based polyphenols, compounds 1-8, were isolated from the wood of Artocarpus heterophyllus. These compounds, which have previously been shown not to inhibit tyrosinase activity, were found to be active inhibitors of the in vivo melanin biosynthesis in B16 melanoma cells, with little or no cytotoxicity. To clarify the structural requirement for inhibition, some structure-activity relationships were studied, in comparison with related compounds lacking prenyl side chains. Our experiments indicate that both prenyl and OH groups, as well as the type of substitution pattern, are crucial for the inhibition of melanin production in B16 melanoma cells.

Evaluating How the Computer-Supported Collaborative Learning Community Fosters Critical Reflective Practices

ERIC Educational Resources Information Center

Ma, Ada W.W.

2013-01-01

In recent research, little attention has been paid to issues of methodology and analysis methods to evaluate the quality of the collaborative learning community. To address such issues, an attempt is made to adopt the Activity System Model as an analytical framework to examine the relationship between computer supported collaborative learning…

Relationship between Trustworthiness, Transparency, and Security in Cloud Computing Environments: A Regression Analysis

ERIC Educational Resources Information Center

Ibrahim, Sara

2017-01-01

The insider security threat causes new and dangerous dimensions in cloud computing. Those internal threats are originated from contractors or the business partners' input that have access to the systems. A study of trustworthiness and transparency might assist the organizations to monitor employees' activity more cautiously on cloud technologies…

Design, synthesis and exploring the quantitative structure-activity relationship of some antioxidant flavonoid analogues.

PubMed

Das, Sreeparna; Mitra, Indrani; Batuta, Shaikh; Niharul Alam, Md; Roy, Kunal; Begum, Naznin Ara

2014-11-01

A series of flavonoid analogues were synthesized and screened for the in vitro antioxidant activity through their ability to quench 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical. The activity of these compounds, measured in comparison to the well-known standard antioxidants (29-32), their precursors (38-42) and other bioactive moieties (38-42) resembling partially the flavone skeleton was analyzed further to develop Quantitative Structure-Activity Relationship (QSAR) models using the Genetic Function Approximation (GFA) technique. Based on the essential structural requirements predicted by the QSAR models, some analogues were designed, synthesized and tested for activity. The predicted and experimental activities of these compounds were well correlated. Flavone analogue 20 was found to be the most potent antioxidant. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantitative Structure-Antifungal Activity Relationships for cinnamate derivatives.

PubMed

Saavedra, Laura M; Ruiz, Diego; Romanelli, Gustavo P; Duchowicz, Pablo R

2015-12-01

Quantitative Structure-Activity Relationships (QSAR) are established with the aim of analyzing the fungicidal activities of a set of 27 active cinnamate derivatives. The exploration of more than a thousand of constitutional, topological, geometrical and electronic molecular descriptors, which are calculated with Dragon software, leads to predictions of the growth inhibition on Pythium sp and Corticium rolfsii fungi species, in close agreement to the experimental values extracted from the literature. A set containing 21 new structurally related cinnamate compounds is prepared. The developed QSAR models are applied to predict the unknown fungicidal activity of this set, showing that cinnamates like 38, 28 and 42 are expected to be highly active for Pythium sp, while this is also predicted for 28 and 34 in C. rolfsii. Copyright © 2015 Elsevier Inc. All rights reserved.

Spaceborne Processor Array

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Schatzel, Donald V.; Whitaker, William D.; Sterling, Thomas

2008-01-01

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

Structure-activity relationships in carbohydrates revealed by their hydration.

PubMed

Maugeri, Laura; Busch, Sebastian; McLain, Sylvia E; Pardo, Luis Carlos; Bruni, Fabio; Ricci, Maria Antonietta

2017-06-01

One of the more intriguing aspects of carbohydrate chemistry is that despite having very similar molecular structures, sugars have very different properties. For instance, there is a sensible difference in sweet taste between glucose and trehalose, even though trehalose is a disaccharide that comprised two glucose units, suggesting a different ability of these two carbohydrates to bind to sweet receptors. Here we have looked at the hydration of specific sites and at the three-dimensional configuration of water molecules around three carbohydrates (glucose, cellobiose, and trehalose), combining neutron diffraction data with computer modelling. Results indicate that identical chemical groups can have radically different hydration patterns depending on their location on a given molecule. These differences can be linked with the specific activity of glucose, cellobiose, and trehalose as a sweet substance, as building block of cellulose fiber, and as a bioprotective agent, respectively. This article is part of a Special Issue entitled "Recent Advances in Bionanomaterials" Guest Editors: Dr. Marie-Louise Saboungi and Dr. Samuel D. Bader. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative structure-activity relationship analysis and virtual screening studies for identifying HDAC2 inhibitors from known HDAC bioactive chemical libraries.

PubMed

Pham-The, H; Casañola-Martin, G; Diéguez-Santana, K; Nguyen-Hai, N; Ngoc, N T; Vu-Duc, L; Le-Thi-Thu, H

2017-03-01

Histone deacetylases (HDAC) are emerging as promising targets in cancer, neuronal diseases and immune disorders. Computational modelling approaches have been widely applied for the virtual screening and rational design of novel HDAC inhibitors. In this study, different machine learning (ML) techniques were applied for the development of models that accurately discriminate HDAC2 inhibitors form non-inhibitors. The obtained models showed encouraging results, with the global accuracy in the external set ranging from 0.83 to 0.90. Various aspects related to the comparison of modelling techniques, applicability domain and descriptor interpretations were discussed. Finally, consensus predictions of these models were used for screening HDAC2 inhibitors from four chemical libraries whose bioactivities against HDAC1, HDAC3, HDAC6 and HDAC8 have been known. According to the results of virtual screening assays, structures of some hits with pair-isoform-selective activity (between HDAC2 and other HDACs) were revealed. This study illustrates the power of ML-based QSAR approaches for the screening and discovery of potent, isoform-selective HDACIs.

A parallel-vector algorithm for rapid structural analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1990-01-01

A fast, accurate Choleski method for the solution of symmetric systems of linear equations is presented. This direct method is based on a variable-band storage scheme and takes advantage of column heights to reduce the number of operations in the Choleski factorization. The method employs parallel computation in the outermost DO-loop and vector computation via the 'loop unrolling' technique in the innermost DO-loop. The method avoids computations with zeros outside the column heights, and as an option, zeros inside the band. The close relationship between Choleski and Gauss elimination methods is examined. The minor changes required to convert the Choleski code to a Gauss code to solve non-positive-definite symmetric systems of equations are identified. The results for two large-scale structural analyses performed on supercomputers, demonstrate the accuracy and speed of the method.

A parallel-vector algorithm for rapid structural analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1990-01-01

A fast, accurate Choleski method for the solution of symmetric systems of linear equations is presented. This direct method is based on a variable-band storage scheme and takes advantage of column heights to reduce the number of operations in the Choleski factorization. The method employs parallel computation in the outermost DO-loop and vector computation via the loop unrolling technique in the innermost DO-loop. The method avoids computations with zeros outside the column heights, and as an option, zeros inside the band. The close relationship between Choleski and Gauss elimination methods is examined. The minor changes required to convert the Choleski code to a Gauss code to solve non-positive-definite symmetric systems of equations are identified. The results for two large scale structural analyses performed on supercomputers, demonstrate the accuracy and speed of the method.

Using Theoretical Descriptors in Structural Activity Relationships: 4. Molecular Orbital Basicity and Electrostatic Basicity

DTIC Science & Technology

1988-11-01

rates.6 The Hammet equation , also called the Linear Free Energy Relationship (LFER) because of the relationship of the Gibb’s Free Energy to the... equations for numerous biological and physicochemical properties. Linear Solvation Enery Relationship (LSER), a sub-set of QSAR have been used by...originates from thermodynamics, where Hammet recognized the relationship of structure to the Gibb’s Free Energy, and ultimately to equilibria and reaction

Developing sensor activity relationships for the JPL electronic nose sensors using molecular modeling and QSAR techniques

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Jewell, A. D.; Zhou, H.; Manatt, K.; Kisor, A. K.

2005-01-01

We report a Quantitative Structure-Activity Relationships (QSAR) study using Genetic Function Approximations (GFA) to describe the polymer-carbon composite sensor activities in the JPL Electronic Nose, when exposed to chemical vapors at parts-per-million concentration levels.

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

PubMed Central

2012-01-01

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure–activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein–ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance. PMID:22339582

Thermoviscoplastic nonlinear constitutive relationships for structural analysis of high temperature metal matrix composites

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1985-01-01

A set of thermoviscoplastic nonlinear constitutive relationships (1VP-NCR) is presented. The set was developed for application to high temperature metal matrix composites (HT-MMC) and is applicable to thermal and mechanical properties. Formulation of the TVP-NCR is based at the micromechanics level. The TVP-NCR are of simple form and readily integrated into nonlinear composite structural analysis. It is shown that the set of TVP-NCR is computationally effective. The set directly predicts complex materials behavior at all levels of the composite simulation, from the constituent materials, through the several levels of composite mechanics, and up to the global response of complex HT-MMC structural components.

Improving Learners' Oral Fuency through Computer-Mediated Emotional Intelligence Activities

ERIC Educational Resources Information Center

Abdolrezapour, Parisa

2017-01-01

Previous studies have shown that emotional intelligence (henceforth, EI) has a significant impact on important life outcomes (e.g., mental and physical health, academic achievement, work performance, and social relationships). This study aimed to see whether there is any relationship between EI and English as a foreign language (EFL) learners'…

Synthesis, structure-activity relationships, and in vivo evaluation of N3-phenylpyrazinones as novel corticotropin-releasing factor-1 (CRF1) receptor antagonists.

PubMed

Hartz, Richard A; Ahuja, Vijay T; Arvanitis, Argyrios G; Rafalski, Maria; Yue, Eddy W; Denhart, Derek J; Schmitz, William D; Ditta, Jonathan L; Deskus, Jeffrey A; Brenner, Allison B; Hobbs, Frank W; Payne, Joseph; Lelas, Snjezana; Li, Yu-Wen; Molski, Thaddeus F; Mattson, Gail K; Peng, Yong; Wong, Harvey; Grace, James E; Lentz, Kimberley A; Qian-Cutrone, Jingfang; Zhuo, Xiaoliang; Shu, Yue-Zhong; Lodge, Nicholas J; Zaczek, Robert; Combs, Andrew P; Olson, Richard E; Bronson, Joanne J; Mattson, Ronald J; Macor, John E

2009-07-23

Evidence suggests that corticotropin-releasing factor-1 (CRF(1)) receptor antagonists may offer therapeutic potential for the treatment of diseases associated with elevated levels of CRF such as anxiety and depression. A pyrazinone-based chemotype of CRF(1) receptor antagonists was discovered. Structure-activity relationship studies led to the identification of numerous potent analogues including 12p, a highly potent and selective CRF(1) receptor antagonist with an IC(50) value of 0.26 nM. The pharmacokinetic properties of 12p were assessed in rats and Cynomolgus monkeys. Compound 12p was efficacious in the defensive withdrawal test (an animal model of anxiety) in rats. The synthesis, structure-activity relationships and in vivo properties of compounds within the pyrazinone chemotype are described.

Design, Synthesis, and Biological and Structural Evaluations of Novel HIV-1 Protease Inhibitors To Combat Drug Resistance

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

Parai, Maloy Kumar; Huggins, David J.; Cao, Hong

2012-09-11

A series of new HIV-1 protease inhibitors (PIs) were designed using a general strategy that combines computational structure-based design with substrate-envelope constraints. The PIs incorporate various alcohol-derived P2 carbamates with acyclic and cyclic heteroatomic functionalities into the (R)-hydroxyethylamine isostere. Most of the new PIs show potent binding affinities against wild-type HIV-1 protease and three multidrug resistant (MDR) variants. In particular, inhibitors containing the 2,2-dichloroacetamide, pyrrolidinone, imidazolidinone, and oxazolidinone moieties at P2 are the most potent with Ki values in the picomolar range. Several new PIs exhibit nanomolar antiviral potencies against patient-derived wild-type viruses from HIV-1 clades A, B, and Cmore » and two MDR variants. Crystal structure analyses of four potent inhibitors revealed that carbonyl groups of the new P2 moieties promote extensive hydrogen bond interactions with the invariant Asp29 residue of the protease. These structure-activity relationship findings can be utilized to design new PIs with enhanced enzyme inhibitory and antiviral potencies.« less

The effect of psychosocial stress on muscle activity during computer work: Comparative study between desktop computer and mobile computing products.

PubMed

Taib, Mohd Firdaus Mohd; Bahn, Sangwoo; Yun, Myung Hwan

2016-06-27

The popularity of mobile computing products is well known. Thus, it is crucial to evaluate their contribution to musculoskeletal disorders during computer usage under both comfortable and stressful environments. This study explores the effect of different computer products' usages with different tasks used to induce psychosocial stress on muscle activity. Fourteen male subjects performed computer tasks: sixteen combinations of four different computer products with four different tasks used to induce stress. Electromyography for four muscles on the forearm, shoulder and neck regions and task performances were recorded. The increment of trapezius muscle activity was dependent on the task used to induce the stress where a higher level of stress made a greater increment. However, this relationship was not found in the other three muscles. Besides that, compared to desktop and laptop use, the lowest activity for all muscles was obtained during the use of a tablet or smart phone. The best net performance was obtained in a comfortable environment. However, during stressful conditions, the best performance can be obtained using the device that a user is most comfortable with or has the most experience with. Different computer products and different levels of stress play a big role in muscle activity during computer work. Both of these factors must be taken into account in order to reduce the occurrence of musculoskeletal disorders or problems.

Impacts of mothers' occupation status and parenting styles on levels of self-control, addiction to computer games, and educational progress of adolescents.

PubMed

Abedini, Yasamin; Zamani, Bibi Eshrat; Kheradmand, Ali; Rajabizadeh, Ghodratollah

2012-01-01

Addiction to computer (video) games in adolescents and its relationship with educational progress has recently attracted the attention of rearing and education experts as well as organizations and institutes involved in physical and mental health. The current research attempted to propose a structural model of the relationships between parenting styles, mothers' occupation status, and addiction to computer games, self-control, and educational progress of secondary school students. Using multistage cluster random sampling, 500 female and male secondary school students in Kerman (Iran) were selected and studied. The research tools included self-control, parenting styles, and addiction to computer games questionnaires and a self-made questionnaire containing demographic details. The data was analyzed using exploratory factor analysis, Cronbach's alpha coefficient and route analysis (in LISREL). We found self-control to have a linking role in the relationship between four parenting styles and educational progress. Mothers' occupation status was directly and significantly correlated with addiction to computer games. Although four parenting styles directly and significantly affected addiction to computer games, the findings did not support the linking role of addiction to computer games in the relationship between four parenting styles and educational progress. In agreement with previous studies, the current research reflected the impact of four parenting styles on self-control, addiction to computer games, and educational progress of students. Among the parenting styles, authoritative style can affect the severity of addiction to computer games through self-control development. It can thus indirectly influence the educational progress of students. Parents are recommended to use authoritative parenting style to help both self-management and psychological health of their children. The employed mothers are also recommended to have more supervision and control on the degree and type of computer games selected by their children.

Impacts of Mothers’ Occupation Status and Parenting Styles on Levels of Self-Control, Addiction to Computer Games, and Educational Progress of Adolescents

PubMed Central

Abedini, Yasamin; Zamani, Bibi Eshrat; Kheradmand, Ali; Rajabizadeh, Ghodratollah

2012-01-01

Background Addiction to computer (video) games in adolescents and its relationship with educational progress has recently attracted the attention of rearing and education experts as well as organizations and institutes involved in physical and mental health. The current research attempted to propose a structural model of the relationships between parenting styles, mothers’ occupation status, and addiction to computer games, self-control, and educational progress of secondary school students. Methods Using multistage cluster random sampling, 500 female and male secondary school students in Kerman (Iran) were selected and studied. The research tools included self-control, parenting styles, and addiction to computer games questionnaires and a self-made questionnaire containing demographic details. The data was analyzed using exploratory factor analysis, Cronbach’s alpha coefficient and route analysis (in LISREL). Findings We found self-control to have a linking role in the relationship between four parenting styles and educational progress. Mothers’ occupation status was directly and significantly correlated with addiction to computer games. Although four parenting styles directly and significantly affected addiction to computer games, the findings did not support the linking role of addiction to computer games in the relationship between four parenting styles and educational progress. Conclusion In agreement with previous studies, the current research reflected the impact of four parenting styles on self-control, addiction to computer games, and educational progress of students. Among the parenting styles, authoritative style can affect the severity of addiction to computer games through self-control development. It can thus indirectly influence the educational progress of students. Parents are recommended to use authoritative parenting style to help both self-management and psychological health of their children. The employed mothers are also recommended to have more supervision and control on the degree and type of computer games selected by their children. PMID:24494143

Stimulus-dependent spiking relationships with the EEG

PubMed Central

Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

Toward high-resolution computational design of helical membrane protein structure and function

PubMed Central

Barth, Patrick; Senes, Alessandro

2016-01-01

The computational design of α-helical membrane proteins is still in its infancy but has made important progress. De novo design has produced stable, specific and active minimalistic oligomeric systems. Computational re-engineering can improve stability and modulate the function of natural membrane proteins. Currently, the major hurdle for the field is not computational, but the experimental characterization of the designs. The emergence of new structural methods for membrane proteins will accelerate progress PMID:27273630

Estimated activity patterns in British 45 year olds: cross-sectional findings from the 1958 British birth cohort.

PubMed

Parsons, T J; Thomas, C; Power, C

2009-08-01

To investigate patterns of, and associations between, physical activity at work and in leisure time, television viewing and computer use. 4531 men and 4594 women with complete plausible data, age 44-45 years, participating in the 1958 British birth cohort study. Physical activity, television viewing and computer use (hours/week) were estimated using a self-complete questionnaire and intensity (MET hours/week) derived for physical activity. Relationships were investigated using linear regression and chi(2) tests. From a target sample of 11,971, 9223 provided information on physical activity, of whom 75 and 47% provided complete and plausible activity data on work and leisure time activity respectively. Men and women spent a median of 40.2 and 34.2 h/week, respectively in work activity, and 8.3 and 5.8 h/week in leisure activity. Half of all participants watched television for > or =2 h/day, and half used a computer for <1 h/day. Longer work hours were not associated with a shorter duration of leisure activity, but were associated with a shorter duration of computer use (men only). In men, higher work MET hours were associated with higher leisure-time MET hours, and shorter durations of television viewing and computer use. Watching more television was related to fewer hours or MET hours of leisure activity, as was longer computer use in men. Longer computer use was related to more hours (or MET hours) in leisure activities in women. Physical activity levels at work and in leisure time in mid-adulthood are low. Television viewing (and computer use in men) may compete with leisure activity for time, whereas longer duration of work hours is less influential. To change active and sedentary behaviours, better understanding of barriers and motivators is needed.

Structure-activity relationship of crustacean peptide hormones.

PubMed

Katayama, Hidekazu

2016-01-01

In crustaceans, various physiological events, such as molting, vitellogenesis, and sex differentiation, are regulated by peptide hormones. To understanding the functional sites of these hormones, many structure-activity relationship (SAR) studies have been published. In this review, the author focuses the SAR of crustacean hyperglycemic hormone-family peptides and androgenic gland hormone and describes the detailed results of our and other research groups. The future perspectives will be also discussed.

Incorporating Modeling and Simulations in Undergraduate Biophysical Chemistry Course to Promote Understanding of Structure-Dynamics-Function Relationships in Proteins

ERIC Educational Resources Information Center

Hati, Sanchita; Bhattacharyya, Sudeep

2016-01-01

A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and…

Computational Studies of Free Radical-Scavenging Properties of Phenolic Compounds

PubMed Central

Alov, Petko; Tsakovska, Ivanka; Pajeva, Ilza

2015-01-01

For more than half a century free radical-induced alterations at cellular and organ levels have been investigated as a probable underlying mechanism of a number of adverse health conditions. Consequently, significant research efforts have been spent for discovering more effective and potent antioxidants / free radical scavengers for treatment of these adverse conditions. Being by far the most used antioxidants among natural and synthetic compounds, mono- and polyphenols have been the focus of both experimental and computational research on mechanisms of free radical scavenging. Quantum chemical studies have provided a significant amount of data on mechanisms of reactions between phenolic compounds and free radicals outlining a number of properties with a key role for the radical scavenging activity and capacity of phenolics. The obtained quantum chemical parameters together with other molecular descriptors have been used in quantitative structure-activity relationship (QSAR) analyses for the design of new more effective phenolic antioxidants and for identification of the most useful natural antioxidant phenolics. This review aims at presenting the state of the art in quantum chemical and QSAR studies of phenolic antioxidants and at analysing the trends observed in the field in the last decade. PMID:25547098

Computational studies of free radical-scavenging properties of phenolic compounds.

PubMed

Alov, Petko; Tsakovska, Ivanka; Pajeva, Ilza

2015-01-01

For more than half a century free radical-induced alterations at cellular and organ levels have been investigated as a probable underlying mechanism of a number of adverse health conditions. Consequently, significant research efforts have been spent for discovering more effective and potent antioxidants / free radical scavengers for treatment of these adverse conditions. Being by far the most used antioxidants among natural and synthetic compounds, mono- and polyphenols have been the focus of both experimental and computational research on mechanisms of free radical scavenging. Quantum chemical studies have provided a significant amount of data on mechanisms of reactions between phenolic compounds and free radicals outlining a number of properties with a key role for the radical scavenging activity and capacity of phenolics. The obtained quantum chemical parameters together with other molecular descriptors have been used in quantitative structure-activity relationship (QSAR) analyses for the design of new more effective phenolic antioxidants and for identification of the most useful natural antioxidant phenolics. This review aims at presenting the state of the art in quantum chemical and QSAR studies of phenolic antioxidants and at analysing the trends observed in the field in the last decade.

Virtual reality and the psyche. Some psychoanalytic approaches to media addiction.

PubMed

Weisel, Anja

2015-04-01

This paper explores the ramifications of excessive use of media on personality development, the development of symbolic and thinking functions and on psychic reality. In doing so, the questions of whether there are specific media objects possessing an intrinsic symbolic quality, and which attachments in the inner world of a child/adolescent can be mobilized or destroyed are discussed. By selecting specific material, computer gamers use their game to activate the field of a personal psychic reality. Hereby, they attempt some kind of self-healing. However, after leaving the game, conflicts and traumata re-enacted but unresolved in the game disappear from their temporary representation without generating any resonance in the gamer's psychic experience. Consequently, although states of mind and affects are activated in the computer game, their processing and integration fail; the game results in a compulsive repetition. The construction and consolidation of retrievable maturation and structural development, the representation of the unrepresentable, succeed in the context of the triangulating analytic relationship, initially through a jointly performed symbolic and narrative re-experience or the recreation of the game. Theoretical considerations are illustrated by means of clinical vignettes. © 2015, The Society of Analytical Psychology.

Relationship between Chemical Structure and Antimicrobial Activities of Isothiocyanates from Cruciferous Vegetables against Oral Pathogens.

PubMed

Ko, Mi-Ok; Kim, Mi-Bo; Lim, Sang-Bin

2016-12-28

We evaluated the potentials of 10 isothiocyanates (ITCs) from cruciferous vegetables and radish root hydrolysate for inhibiting the growth of oral pathogens, with an emphasis on assessing any structure-function relationship. Structural differences in ITCs impacted their antimicrobial activities against oral pathogens differently. The indolyl ITC (indol-3-carbinol) was the most potent inhibitor of the growth of oral pathogens, followed by aromatic ITCs (benzyl ITC (BITC) and phenylethyl ITC (PEITC)) and aliphatic ITCs (erucin, iberin, and sulforaphene). Sulforaphene, which is similar in structure, but has one double bond, showed higher antimicrobial activity than sulforaphane. Erucin, which has a thiol group, showed higher antimicrobial activity than sulforaphane, which has a sulfinyl group. BITC and iberin with a short chain exhibited higher antimicrobial potential than PEITC and sulforaphane with a longer chain, respectively. ITCs have strong antimicrobial activities and may be useful in the prevention and management of dental caries.

Digital Morphing Wing: Active Wing Shaping Concept Using Composite Lattice-Based Cellular Structures.

PubMed

Jenett, Benjamin; Calisch, Sam; Cellucci, Daniel; Cramer, Nick; Gershenfeld, Neil; Swei, Sean; Cheung, Kenneth C

2017-03-01

We describe an approach for the discrete and reversible assembly of tunable and actively deformable structures using modular building block parts for robotic applications. The primary technical challenge addressed by this work is the use of this method to design and fabricate low density, highly compliant robotic structures with spatially tuned stiffness. This approach offers a number of potential advantages over more conventional methods for constructing compliant robots. The discrete assembly reduces manufacturing complexity, as relatively simple parts can be batch-produced and joined to make complex structures. Global mechanical properties can be tuned based on sub-part ordering and geometry, because local stiffness and density can be independently set to a wide range of values and varied spatially. The structure's intrinsic modularity can significantly simplify analysis and simulation. Simple analytical models for the behavior of each building block type can be calibrated with empirical testing and synthesized into a highly accurate and computationally efficient model of the full compliant system. As a case study, we describe a modular and reversibly assembled wing that performs continuous span-wise twist deformation. It exhibits high performance aerodynamic characteristics, is lightweight and simple to fabricate and repair. The wing is constructed from discrete lattice elements, wherein the geometric and mechanical attributes of the building blocks determine the global mechanical properties of the wing. We describe the mechanical design and structural performance of the digital morphing wing, including their relationship to wind tunnel tests that suggest the ability to increase roll efficiency compared to a conventional rigid aileron system. We focus here on describing the approach to design, modeling, and construction as a generalizable approach for robotics that require very lightweight, tunable, and actively deformable structures.

Digital Morphing Wing: Active Wing Shaping Concept Using Composite Lattice-Based Cellular Structures

PubMed Central

Jenett, Benjamin; Calisch, Sam; Cellucci, Daniel; Cramer, Nick; Gershenfeld, Neil; Swei, Sean

2017-01-01

Abstract We describe an approach for the discrete and reversible assembly of tunable and actively deformable structures using modular building block parts for robotic applications. The primary technical challenge addressed by this work is the use of this method to design and fabricate low density, highly compliant robotic structures with spatially tuned stiffness. This approach offers a number of potential advantages over more conventional methods for constructing compliant robots. The discrete assembly reduces manufacturing complexity, as relatively simple parts can be batch-produced and joined to make complex structures. Global mechanical properties can be tuned based on sub-part ordering and geometry, because local stiffness and density can be independently set to a wide range of values and varied spatially. The structure's intrinsic modularity can significantly simplify analysis and simulation. Simple analytical models for the behavior of each building block type can be calibrated with empirical testing and synthesized into a highly accurate and computationally efficient model of the full compliant system. As a case study, we describe a modular and reversibly assembled wing that performs continuous span-wise twist deformation. It exhibits high performance aerodynamic characteristics, is lightweight and simple to fabricate and repair. The wing is constructed from discrete lattice elements, wherein the geometric and mechanical attributes of the building blocks determine the global mechanical properties of the wing. We describe the mechanical design and structural performance of the digital morphing wing, including their relationship to wind tunnel tests that suggest the ability to increase roll efficiency compared to a conventional rigid aileron system. We focus here on describing the approach to design, modeling, and construction as a generalizable approach for robotics that require very lightweight, tunable, and actively deformable structures. PMID:28289574

Fluid-structure finite-element vibrational analysis

NASA Technical Reports Server (NTRS)

Feng, G. C.; Kiefling, L.

1974-01-01

A fluid finite element has been developed for a quasi-compressible fluid. Both kinetic and potential energy are expressed as functions of nodal displacements. Thus, the formulation is similar to that used for structural elements, with the only differences being that the fluid can possess gravitational potential, and the constitutive equations for fluid contain no shear coefficients. Using this approach, structural and fluid elements can be used interchangeably in existing efficient sparse-matrix structural computer programs such as SPAR. The theoretical development of the element formulations and the relationships of the local and global coordinates are shown. Solutions of fluid slosh, liquid compressibility, and coupled fluid-shell oscillation problems which were completed using a temporary digital computer program are shown. The frequency correlation of the solutions with classical theory is excellent.

Roles of Long-range Electrostatic Domain Interactions and K+ in Phosphoenzyme Transition of Ca2+-ATPase*

PubMed Central

Yamasaki, Kazuo; Daiho, Takashi; Danko, Stefania; Suzuki, Hiroshi

2013-01-01

Sarcoplasmic reticulum Ca2+-ATPase couples the motions and rearrangements of three cytoplasmic domains (A, P, and N) with Ca2+ transport. We explored the role of electrostatic force in the domain dynamics in a rate-limiting phosphoenzyme (EP) transition by a systematic approach combining electrostatic screening with salts, computer analysis of electric fields in crystal structures, and mutations. Low KCl concentration activated and increasing salt above 0.1 m inhibited the EP transition. A plot of the logarithm of the transition rate versus the square of the mean activity coefficient of the protein gave a linear relationship allowing division of the activation energy into an electrostatic component and a non-electrostatic component in which the screenable electrostatic forces are shielded by salt. Results show that the structural change in the transition is sterically restricted, but that strong electrostatic forces, when K+ is specifically bound at the P domain, come into play to accelerate the reaction. Electric field analysis revealed long-range electrostatic interactions between the N and P domains around their hinge. Mutations of the residues directly involved and other charged residues at the hinge disrupted in parallel the electric field and the structural transition. Favorable electrostatics evidently provides a low energy path for the critical N domain motion toward the P domain, overcoming steric restriction. The systematic approach employed here is, in general, a powerful tool for understanding the structural mechanisms of enzymes. PMID:23737524

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.

Security and Interdependency in a Public Cloud: A Game Theoretic Approach

DTIC Science & Technology

2014-08-29

maximum utility can be reached (i.e., Pareto efficiency). However, the examples of perverse incentives and information inequality (where this feedback...interdependent structure. Cloud computing gives way to two types of interdependent relationships: cloud host-to- client and cloud client -to- client ... Client -to- client interdependency is much less studied than to the above-mentioned cloud host-to- client relationship. Although, it can still carry the

A method for transferring NASTRAN data between dissimilar computers. [application to CDC 6000 series, IBM 360-370 series, and Univac 1100 series computers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.

1973-01-01

The NASTRAN computer program is capable of executing on three different types of computers: (1) the CDC 6000 series, (2) the IBM 360-370 series, and (3) the Univac 1100 series. A typical activity requiring transfer of data between dissimilar computers is the analysis of a large structure such as the space shuttle by substructuring. Models of portions of the vehicle which have been analyzed by subcontractors using their computers must be integrated into a model of the complete structure by the prime contractor on his computer. Presently the transfer of NASTRAN matrices or tables between two different types of computers is accomplished by punched cards or a magnetic tape containing card images. These methods of data transfer do not satisfy the requirements for intercomputer data transfer associated with a substructuring activity. To provide a more satisfactory transfer of data, two new programs, RDUSER and WRTUSER, were created.

Synthesis, fungicidal activity, structure-activity relationships (SARs) and density functional theory (DFT) studies of novel strobilurin analogues containing arylpyrazole rings.

PubMed

Liu, Yuanyuan; Lv, Kunzhi; Li, Yi; Nan, Qiuli; Xu, Jinyuan

2018-05-18

A series of novel strobilurin analogues (1a-1f, 2a-2e, 3a-3e) containing arylpyrazole rings were synthesized and characterized by NMR spectroscopy. The structures of 1f, 2b and 3b were also determined by single crystal X-ray diffraction analysis. These analogues were collected together with other twenty-eight similar compounds 4a-4f, 5a-5h, 6a-6h and 7a-7f from our previous studies, for in vitro bioassays and thorough structure-activity relationships (SARs) studies. Most compounds exhibited excellent-to-good fungicidal activity against Rhizoctonia solani, especially 5c, 7a, 6c, and 3b with 98.94%, 83.40%, 71.40% and 65.87% inhibition rates at 0.1 μg mL -1 , respectively, better than commercial pyraclostrobin. Comparative molecular field analysis (CoMFA) was employed to study three-dimensional quantitative structure-activity relationships (3D-QSARs). Density functional theory (DFT) calculation was also carried out to provide more information regarding SARs. The present work provided some hints for developing novel strobilurin fungicides.

Computational challenges of structure-based approaches applied to HIV.

PubMed

Forli, Stefano; Olson, Arthur J

2015-01-01

Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.

Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity.

PubMed

Levatić, Jurica; Pavić, Kristina; Perković, Ivana; Uzelac, Lidija; Ester, Katja; Kralj, Marijeta; Kaiser, Marcel; Rottmann, Matthias; Supek, Fran; Zorc, Branka

2018-02-25

Primaquine (PQ) is a commonly used drug that can prevent the transmission of Plasmodium falciparum malaria, however toxicity limits its use. We prepared five groups of PQ derivatives: amides 1a-k, ureas 2a-k, semicarbazides 3a,b, acylsemicarbazides 4a-k and bis-ureas 5a-v, and evaluated them for antimalarial activity in vitro against the erythrocytic stage of P. falciparum NF54. Particular substituents, such as trityl (in 2j and 5r) and methoxybenzhydryl (in 3b and 5v) were associated with a favorable cytotoxicity-to-activity ratio. To systematically link structural features of PQ derivatives to antiplasmodial activity, we performed a quantitative structure-activity relationship (QSAR) study using the Support Vector Machines machine learning method. This yielded a highly accurate statistical model (R 2  = 0.776 in cross-validation), which was used to prioritize novel candidate compounds. Seven novel PQ-ureidoamides 10a-g were synthesized and evaluated for activity, highlighting the benzhydryl ureidoamides 10e and 10f derived from p-chlorophenylglycine. Further experiments on human cell lines revealed that 10e and 10f are an order of magnitude less toxic than PQ in vitro while having antimalarial activity indistinguishable from PQ. The toxicity profile of novel compounds 10 toward human cells was particularly favorable when the glucose-6-phosphate dehydrogenase (G6PD) was inhibited, while toxicity of PQ was exacerbated by G6PD inhibition. Our work therefore highlights promising lead compounds for the development of effective antimalarial drugs that may also be safer for G6PD-deficient patients. In addition, we provide computational inferences of antimalarial activity and cytotoxicity for thousands of PQ-like molecular structures. Copyright © 2018 Elsevier Masson SAS. 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.

The use of QSAR methods for determination of n-octanol/water partition coefficient using the example of hydroxyester HE-1

NASA Astrophysics Data System (ADS)

Guziałowska-Tic, Joanna

2017-10-01

According to the Directive of the European Parliament and of the Council concerning the protection of animals used for scientific purposes, the number of experiments involving the use of animals needs to be reduced. The methods which can replace animal testing include computational prediction methods, for instance, the quantitative structure-activity relationships (QSAR). These methods are designed to find a cohesive relationship between differences in the values of the properties of molecules and the biological activity of a series of test compounds. This paper compares the results of the author's own results of examination on the n-octanol/water coefficient for the hydroxyester HE-1 with those generated by means of three models: Kowwin, MlogP, AlogP. The test results indicate that, in the case of molecular similarity, the highest determination coefficient was obtained for the model MlogP and the lowest root-mean square error was obtained for the Kowwin method. When comparing the mean logP value obtained using the QSAR models with the value resulting from the author's own experiments, it was observed that the best conformity was that recorded for the model AlogP, where relative error was 15.2%.

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

Computational insights into the interaction of small molecule inhibitors with HRI kinase domain.

PubMed

Palrecha, Sourabh; Lakade, Dushant; Kulkarni, Abhijeet; Pal, Jayanta K; Joshi, Manali

2018-05-07

The Heme-Regulated Inhibitor (HRI) kinase regulates globin synthesis in a heme-dependent manner in reticulocytes and erythroid cells in bone marrow. Inhibitors of HRI have been proposed to lead to an increased amount of haemoglobin, benefitting anaemia patients. A series of indeno[1,2-c]pyrazoles were discovered to be the first known in vitro inhibitors of HRI. However, the structural mechanism of inhibition is yet to be understood. The aim of this study was to unravel the binding mechanism of these inhibitors using molecular dynamic simulations and docking. The docking scores were observed to correlate well with experimentally determined pIC 50 values. The inhibitors were observed to bind in the ATP-binding site forming hydrogen bonds with the hinge region and van der Waals interactions with non-polar residues in the binding site. Further, quantitative structure-activity relationship (QSAR) studies were performed to correlate the structural features of the inhibitors with their biological activity. The developed QSAR models were found to be statistically significant in terms of internal and external predictabilities. The presence of chlorine atoms and the hydroxymethyl groups were found to correlate with higher activity. The identified binding modes and the descriptors can support future rational identification of more potent and selective small molecule inhibitors for this kinase which are of therapeutic importance in the context of various human pathological disorders.

Structure-activity relationships between sterols and their thermal stability in oil matrix.

PubMed

Hu, Yinzhou; Xu, Junli; Huang, Weisu; Zhao, Yajing; Li, Maiquan; Wang, Mengmeng; Zheng, Lufei; Lu, Baiyi

2018-08-30

Structure-activity relationships between 20 sterols and their thermal stabilities were studied in a model oil system. All sterol degradations were found to be consistent with a first-order kinetic model with determination of coefficient (R 2 ) higher than 0.9444. The number of double bonds in the sterol structure was negatively correlated with the thermal stability of sterol, whereas the length of the branch chain was positively correlated with the thermal stability of sterol. A quantitative structure-activity relationship (QSAR) model to predict thermal stability of sterol was developed by using partial least squares regression (PLSR) combined with genetic algorithm (GA). A regression model was built with R 2 of 0.806. Almost all sterol degradation constants can be predicted accurately with R 2 of cross-validation equals to 0.680. Four important variables were selected in optimal QSAR model and the selected variables were observed to be related with information indices, RDF descriptors, and 3D-MoRSE descriptors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Augmented multivariate image analysis applied to quantitative structure-activity relationship modeling of the phytotoxicities of benzoxazinone herbicides and related compounds on problematic weeds.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2013-09-11

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.

Application of data mining approaches to drug delivery.

PubMed

Ekins, Sean; Shimada, Jun; Chang, Cheng

2006-11-30

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.

Correlation between average frequency and RA value (rise time/amplitude) for crack classification of reinforced concrete beam using acoustic emission technique

NASA Astrophysics Data System (ADS)

Noorsuhada, M. N.; Abdul Hakeem, Z.; Soffian Noor, M. S.; Noor Syafeekha, M. S.; Azmi, I.

2017-12-01

Health monitoring of structures during their service life become a vital thing as it provides crucial information regarding the performance and condition of the structures. Acoustic emission (AE) is one of the non-destructive techniques (NDTs) that could be used to monitor the performance of the structures. Reinforced concrete (RC) beam associated with AE monitoring was monotonically loaded to failure under three-point loading. Correlation between average frequency and RA value (rise time / amplitude) was computed. The relationship was established to classify the crack types that propagated in the RC beam. The crack was classified as tensile crack and shear crack. It was found that the relationship is well matched with the actual crack pattern that appeared on the beam surface. Hence, this relationship is useful for prediction of the crack occurrence in the beam and its performance can be determined.

Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments

NASA Astrophysics Data System (ADS)

Yao, Xiuya; Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina; Plassard, Andrew; Harrigan, Rob L.; Mawn, Louise A.; Landman, Bennett A.

2017-02-01

Eye diseases and visual impairment affect millions of Americans and induce billions of dollars in annual economic burdens. Expounding upon existing knowledge of eye diseases could lead to improved treatment and disease prevention. This research investigated the relationship between structural metrics of the eye orbit and visual function measurements in a cohort of 470 patients from a retrospective study of ophthalmology records for patients (with thyroid eye disease, orbital inflammation, optic nerve edema, glaucoma, intrinsic optic nerve disease), clinical imaging, and visual function assessments. Orbital magnetic resonance imaging (MRI) and computed tomography (CT) images were retrieved and labeled in 3D using multi-atlas label fusion. Based on the 3D structures, both traditional radiology measures (e.g., Barrett index, volumetric crowding index, optic nerve length) and novel volumetric metrics were computed. Using stepwise regression, the associations between structural metrics and visual field scores (visual acuity, functional acuity, visual field, functional field, and functional vision) were assessed. Across all models, the explained variance was reasonable (R2 0.1-0.2) but highly significant (p < 0.001). Instead of analyzing a specific pathology, this study aimed to analyze data across a variety of pathologies. This approach yielded a general model for the connection between orbital structural imaging biomarkers and visual function.

Structure-activity relationships of rosiglitazone for peroxisome proliferator-activated receptor gamma transrepression.

PubMed

Toyota, Yosuke; Nomura, Sayaka; Makishima, Makoto; Hashimoto, Yuichi; Ishikawa, Minoru

2017-06-15

Anti-inflammatory effects of peroxisome proliferator-activated receptor gamma (PPRAγ) ligands are thought to be largely due to PPARγ-mediated transrepression. Thus, transrepression-selective PPARγ ligands without agonistic activity or with only partial agonistic activity should exhibit anti-inflammatory properties with reduced side effects. Here, we investigated the structure-activity relationships (SARs) of PPARγ agonist rosiglitazone, focusing on transrepression activity. Alkenic analogs showed slightly more potent transrepression with reduced efficacy of transactivating agonistic activity. Removal of the alkyl group on the nitrogen atom improved selectivity for transrepression over transactivation. Among the synthesized compounds, 3l exhibited stronger transrepressional activity (IC 50 : 14μM) and weaker agonistic efficacy (11%) than rosiglitazone or pioglitazone. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationship between structure and antiproliferative activity of polymethoxyflavones towards HL60 cells.

PubMed

Kawaii, Satoru; Ikuina, Tomoyasu; Hikima, Takeshi; Tokiwano, Tetsuo; Yoshizawa, Yuko

2012-12-01

As part of our continuing investigation of polymethoxyflavone (PMF) derivatives as potential anticancer substances, a series of PMF derivatives was synthesized. The synthesized compounds were evaluated for cytotoxicity against the promyelocytic leukemic HL60 cell line, and structure-activity relationship correlations were investigated along with previously isolated PMFs from the peel of king orange (Citrus nobilis). 7,3'-Dimethoxyflavone demonstrated the most potent activity among the synthetic PMFs. Consideration of correlation between the methoxylation pattern and antiproliferative activity revealed the importance of the 3'-methoxyl group and the higher degree of methoxylation on the A-ring moiety of PMFs.

Ring-substituted 4-hydroxy-1H-quinolin-2-ones: preparation and biological activity.

PubMed

Jampilek, Josef; Musiol, Robert; Pesko, Matus; Kralova, Katarina; Vejsova, Marcela; Carroll, James; Coffey, Aidan; Finster, Jacek; Tabak, Dominik; Niedbala, Halina; Kozik, Violetta; Polanski, Jaroslaw; Csollei, Jozef; Dohnal, Jiri

2009-03-13

In the study, a series of twelve ring-substituted 4-hydroxy-1H-quinolin-2-one derivatives were prepared. The procedures for synthesis of the compounds are presented. The compounds were analyzed using RP-HPLC to determine lipophilicity and tested for their photosynthesis-inhibiting activity using spinach (Spinacia oleracea L.) chloroplasts. All the synthesized compounds were also evaluated for antifungal activity using in vitro screening with eight fungal strains. For all the compounds, the relationships between the lipophilicity and the chemical structure of the studied compounds are discussed, as well as their structure-activity relationships (SAR).

Solid-phase synthesis and structure-activity relationships of novel biarylethers as melanin-concentrating hormone receptor-1 antagonists.

PubMed

Ma, Vu; Bannon, Anthony W; Baumgartner, Jamie; Hale, Clarence; Hsieh, Faye; Hulme, Christopher; Rorrer, Kirk; Salon, John; van Staden, Carlo; Tempest, Paul

2006-10-01

Melanin-concentrating hormone (MCH) is a cyclic 19 amino acid orexigenic neuropeptide. The action of MCH on feeding is thought to involve the activation of its respective G protein-coupled receptor MCH-R1. Consequently, antagonists that block MCH regulated MCH-R1 activity may provide a viable approach to the treatment of diet-induced obesity. This communication reports the discovery of a novel MCH-R1 receptor antagonist, the biarylether 7, identified through high throughput screening. The solid-phase synthesis and structure-activity relationship of related analogs is described.

Measuring ICT Use and Learning Outcomes: Evidence from Recent Econometric Studies

ERIC Educational Resources Information Center

Biagi, Federico; Loi, Massimo

2013-01-01

Based on PISA 2009 data, this article studies the relationship between students' computer use and their achievement in reading, mathematics and science in 23 countries. After having categorised computer use into a set of different activities according to the skills they involve, we correlate students' PISA test-scores with an index capturing the…

Adolescent computer use and alcohol use: what are the role of quantity and content of computer use?

PubMed

Epstein, Jennifer A

2011-05-01

The purpose of this study was to examine the relationship between computer use and alcohol use among adolescents. In particular, the goal of the research was to determine the role of lifetime drinking and past month drinking on quantity as measured by amount of time on the computer (for school work and excluding school work) and on content as measured by the frequency of a variety of activities on the internet (e.g., e-mail, searching for information, social networking, listen to/download music). Participants (aged 13-17 years and residing in the United States) were recruited via the internet to complete an anonymous survey online using a popular survey tool (N=270). Their average age was 16 and the sample was predominantly female (63% girls). A series of analyses was conducted with the computer use measures as dependent variables (hours on the computer per week for school work and excluding school work; various internet activities including e-mail, searching for information, social networking, listen to/download music) controlling for gender, age, academic performance and age of first computer use. Based on the results, past month drinkers used the computer more hours per week excluding school work than those who did not. As expected, there were no differences in hours based on alcohol use for computer use for school work. Drinking also had relationships with more frequent social networking and listening to/downloading music. These findings suggest that both quantity and content of computer use were related to adolescent drinking. Copyright © 2010 Elsevier Ltd. All rights reserved.

Investigation on Quantitative Structure Activity Relationships of a Series of Inducible Nitric Oxide.

PubMed

Sharma, Mukesh C; Sharma, S

2016-12-01

A series of 2-dihydro-4-quinazolin with potent highly selective inhibitors of inducible nitric oxide synthase activities was subjected to quantitative structure activity relationships (QSAR) analysis. Statistically significant equations with high correlation coefficient (r 2  = 0.8219) were developed. The k-nearest neighbor model has showed good cross-validated correlation coefficient and external validation values of 0.7866 and 0.7133, respectively. The selected electrostatic field descriptors the presence of blue ball around R1 and R4 in the quinazolinamine moiety showed electronegative groups favorable for nitric oxide synthase activity. The QSAR models may lead to the structural requirements of inducible nitric oxide compounds and help in the design of new compounds.

On the placement of active members in adaptive truss structures for vibration control

NASA Technical Reports Server (NTRS)

Lu, L.-Y.; Utku, S.; Wada, B. K.

1992-01-01

The problem of optimal placement of active members which are used for vibration control in adaptive truss structures is investigated. The control scheme is based on the method of eigenvalue assignment as a means of shaping the transient response of the controlled adaptive structures, and the minimization of required control action is considered as the optimization criterion. To this end, a performance index which measures the control strokes of active members is formulated in an efficient way. In order to reduce the computation burden, particularly for the case where the locations of active members have to be selected from a large set of available sites, several heuristic searching schemes are proposed for obtaining the near-optimal locations. The proposed schemes significantly reduce the computational complexity of placing multiple active members to the order of that when a single active member is placed.

Identification of fused 16β,17β-oxazinone-estradiol derivatives as a new family of non-estrogenic 17β-hydroxysteroid dehydrogenase type 1 inhibitors.

PubMed

Maltais, René; Trottier, Alexandre; Delhomme, Audrey; Barbeau, Xavier; Lagüe, Patrick; Poirier, Donald

2015-03-26

A new family of cyclic carbamate-estradiol derivatives has been designed to remove the intrinsic estrogenic activity of a parent acyclic compound reported as a potent inhibitor of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1). The synthesis of two series of fused 16β,17β-oxazinone-estradiol derivatives, saturated compounds 7a-d and unsaturated compounds 10a-d, led to the identification of 10b, a 17β-HSD1 inhibitor (IC50 = 1.4 μM) without estrogenic activity in estrogen-sensitive T-47D cells. Interestingly, this compound was found selective over 17β-HSD2 and 17β-HSD12. A computational analysis of inhibitors into 17β-HSD1 by molecular docking also revealed interesting structure-activity relationships that could be helpful in the design of new generation of 16β,17β-oxazinone-estradiol analogs. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Structure-antioxidant activity relationships of flavonoids isolated from the resinous exudate of Heliotropium sinuatum.

PubMed

Modak, Brenda; Contreras, M Leonor; González-Nilo, Fernando; Torres, René

2005-01-17

Relationships between the structural characteristics of flavonoids isolated from the resinous exudate of Heliotropium sinuatum and their antioxidant activity were studied. Radical formation energies, DeltaH of dehydrogenation and spin densities were calculated using DFT methods (B3LYP/6-31G*). Results show that studied flavonoids can be divided into two sets according to their activity. It has been found that antioxidant activity depends both on substitution pattern of hydroxyl groups of the flavonoid skeleton and the presence of an unsaturation at the C2-C3 bond. A good tendency between DeltaH of dehydrogenation and antioxidant activity was established.

Uncovering the structure-function relationship in spider silk

NASA Astrophysics Data System (ADS)

Yarger, Jeffery L.; Cherry, Brian R.; van der Vaart, Arjan

2018-03-01

All spiders produce protein-based biopolymer fibres that we call silk. The most studied of these silks is spider dragline silk, which is very tough and relatively abundant compared with other types of spider silks. Considerable research has been devoted to understanding the relationship between the molecular structure and mechanical properties of spider dragline silks. In this Review, we overview experimental and computational studies that have provided a wealth of detail at the molecular level on the highly conserved repetitive core and terminal regions of spider dragline silk. We also discuss the role of the nanocrystalline β-sheets and amorphous regions in determining the properties of spider silk fibres, endowing them with strength and elasticity. Additionally, we outline imaging techniques and modelling studies that elucidate the importance of the hierarchical structure of silk fibres at the molecular level. These insights into structure-function relationships can guide the reverse engineering of spider silk to enable the production of superior synthetic fibres.

Drug interaction study of flavonoids toward CYP3A4 and their quantitative structure activity relationship (QSAR) analysis for predicting potential effects.

PubMed

Li, Yannan; Ning, Jing; Wang, Yan; Wang, Chao; Sun, Chengpeng; Huo, Xiaokui; Yu, Zhenlong; Feng, Lei; Zhang, Baojing; Tian, Xiangge; Ma, Xiaochi

2018-05-09

The high risk of herb-drug interactions (HDIs) mediated by the herbal medicines and dietary supplements which containing abundant flavonoids had become more and more frequent in our daily life. In our study, the inhibition activities of 44 different structures of flavonoids toward human CYPs were systemically evaluated for the first time. According to our results, a remarkable structure-dependent inhibition behavior toward CYP3A4 was observed in vitro. Some flavonoids such as licoflavone (12) and irilone (30) exhibited the selective inhibition toward CYP3 A4 rather than other major human CYPs. To illustrate the interaction mechanism, the inhibition kinetics of various compounds was further performed. Sophoranone (1), apigenin (10), baicalein (11), 5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone (15), myricetin (23) and kushenol K (38) remarkably inhibited the CYP3 A4-catalyzed bufalin 5'-hydroxylation reaction, with K i values of 2.17 ± 0.29, 6.15 ± 0.39, 9.18 ± 3.40, 2.30 ± 0.36, 5.00 ± 2.77 and 1.35 ± 0.25 μM, respectively. Importantly, compounds 1, 11, 15, 23 and 38 could significantly inhibit the metabolism of some clinical drugs in vitro, and these drug-drug interactions (DDIs) of myricetin (23) or kushenol K (38) with clinical drug diazepam were further verified in human primary hepatocytes, respectively. Finally, a quantitative structure-activity relationship (QSAR) of flavonoids with their inhibitory effects toward CYP3 A4 was established using computational methods. Our findings illustrated the high risk of herb-drug interactions (HDIs) caused by flavonoids and revealed the vital structures requirement of natural flavonoids for the HDIs with clinical drugs eliminated by CYP3 A4. Our research provided the useful guidance to safely and rationally use herbal medicines and dietary supplements containing rich natural flavonoids components. Copyright © 2018 Elsevier B.V. All rights reserved.

Syntactic structure building in the anterior temporal lobe during natural story listening.

PubMed

Brennan, Jonathan; Nir, Yuval; Hasson, Uri; Malach, Rafael; Heeger, David J; Pylkkänen, Liina

2012-02-01

The neural basis of syntax is a matter of substantial debate. In particular, the inferior frontal gyrus (IFG), or Broca's area, has been prominently linked to syntactic processing, but the anterior temporal lobe has been reported to be activated instead of IFG when manipulating the presence of syntactic structure. These findings are difficult to reconcile because they rely on different laboratory tasks which tap into distinct computations, and may only indirectly relate to natural sentence processing. Here we assessed neural correlates of syntactic structure building in natural language comprehension, free from artificial task demands. Subjects passively listened to Alice in Wonderland during functional magnetic resonance imaging and we correlated brain activity with a word-by-word measure of the amount syntactic structure analyzed. Syntactic structure building correlated with activity in the left anterior temporal lobe, but there was no evidence for a correlation between syntactic structure building and activity in inferior frontal areas. Our results suggest that the anterior temporal lobe computes syntactic structure under natural conditions. Copyright © 2010 Elsevier Inc. All rights reserved.

Synthesis and quantitative structure-antifungal activity relationships of clovane derivatives against Botrytis cinerea.

PubMed

Saiz-Urra, Liane; Racero, Juan C; Macías-Sáchez, Antonio J; Hernández-Galán, Rosario; Hanson, James R; Perez-Gonzalez, Maykel; Collado, Isidro G

2009-03-25

Twenty-three clovane derivatives, nine described here for the first time, bearing substituents on carbon C-2, have been synthesized and evaluated for their in vitro antifungal activity against the phytopathogenic fungus Botrytis cinerea. The results showed that compounds 9, 14, 16, and 18 bearing nitrogen atoms in the chain attached at C-2 displayed potent antifungal activity, whereas mercapto derivatives 13, 19, and 22 displayed low activity. The antifungal activity showed a clear structure-activity relationship (SAR) trend, which confirmed the importance of the nature of the C-2 chain on the antifungal activity. On the basis of these observations, the metabolism of compounds 8 and 14 by the fungus B. cinerea, and the metabolism of other clovanes by this fungus, described previously, a pro-drug action mechanism for 2-alkoxyclovane compounds is proposed. Quantitative structure-activity relationship (QSAR) studies were performed to rationalize the results and to suggest further optimization, using a topological sub-structural molecular design (TOPS-MODE) approach. The model displayed good fit and predictive capability, describing 85.5% of the experimental variance, with a standard deviation of 9.502 and yielding high values of cross-validation determination coefficients (q2CV-LOO = 0.784 and q2boot = 0.673). The most significant variables were the spectral moments weighted by bond dipole moment (Dip), hydrophobicity (Hyd), and the combined dipolarity/polarizability Abraham molecular descriptor (Ab-pi2H).

Structure-activity relationships of the unique and potent agouti-related protein (AGRP)-melanocortin chimeric Tyr-c[beta-Asp-His-DPhe-Arg-Trp-Asn-Ala-Phe-Dpr]-Tyr-NH2 peptide template.

PubMed

Wilczynski, Andrzej; Wilson, Krista R; Scott, Joseph W; Edison, Arthur S; Haskell-Luevano, Carrie

2005-04-21

The melanocortin receptor system consists of endogenous agonists, antagonists, G-protein coupled receptors, and auxiliary proteins that are involved in the regulation of complex physiological functions such as energy and weight homeostasis, feeding behavior, inflammation, sexual function, pigmentation, and exocrine gland function. Herein, we report the structure-activity relationship (SAR) of a new chimeric hAGRP-melanocortin agonist peptide template Tyr-c[beta-Asp-His-DPhe-Arg-Trp-Asn-Ala-Phe-Dpr]-Tyr-NH(2) that was characterized using amino acids previously reported in other melanocortin agonist templates. Twenty peptides were examined in this study, and six peptides were selected for (1)H NMR and computer-assisted molecular modeling structural analysis. The most notable results include the identification that modification of the chimeric template at the His position with Pro and Phe resulted in ligands that were nM mouse melanocortin-3 receptor (mMC3R) antagonists and nM mouse melanocortin-4 receptor (mMC4R) agonists. The peptides Tyr-c[beta-Asp-His-DPhe-Ala-Trp-Asn-Ala-Phe-Dpr]-Tyr-NH(2) and Tyr-c[beta-Asp-His-DNal(1')-Arg-Trp-Asn-Ala-Phe-Dpr]-Tyr-NH(2) resulted in 730- and 560-fold, respectively, mMC4R versus mMC3R selective agonists that also possessed nM agonist potency at the mMC1R and mMC5R. Structural studies identified a reverse turn occurring in the His-DPhe-Arg-Trp domain, with subtle differences observed that may account for the differences in melanocortin receptor pharmacology. Specifically, a gamma-turn secondary structure involving the DPhe(4) in the central position of the Tyr-c[beta-Asp-Phe-DPhe-Arg-Trp-Asn-Ala-Phe-Dpr]-Tyr-NH(2) peptide may differentiate the mixed mMC3R antagonist and mMC4R agonist pharmacology.

Pediatric obesity and depression: a cross-sectional analysis of absolute BMI as it relates to children's depression index scores in obese 7- to 17-year-old children.

PubMed

Benson, Levi P; Williams, Ronald J; Novick, Marsha B

2013-01-01

Depression and obesity are important in children because they affect health in childhood and later life. The exact relationship between obesity and depression, especially in children, remains undefined. Using a cross-sectional chart review design, our study looked at a weight management clinic-based sample of 117 obese children, 7 to 17 years old, to determine the relationship between absolute BMI and depression as measured by the Children's Depression Index (CDI) while accounting for confounders, such as the child's medical problems, physical activity, and family structure. There was no correlation between depression as measured by the CDI and increasing BMI in obese children seeking weight management. However, we did demonstrate a positive correlation between depression and paternal absence and daily television/computer/video game time. Clinicians should encourage decreasing screen time and might consider family therapy for obese children in families that lack paternal involvement.

We're in This Together: Intentional Design of Social Relationships with AIED Systems

ERIC Educational Resources Information Center

Walker, Erin; Ogan, Amy

2016-01-01

Students' relationships with their peers, teachers, and communities influence the ways in which they approach learning activities and the degree to which they benefit from them. Learning technologies, ranging from humanoid robots to text-based prompts on a computer screen, have a similar social influence on students. We envision a future in which…

Electron-density descriptors as predictors in quantitative structure--activity/property relationships and drug design.

PubMed

Matta, Chérif F; Arabi, Alya A

2011-06-01

The use of electron density-based molecular descriptors in drug research, particularly in quantitative structure--activity relationships/quantitative structure--property relationships studies, is reviewed. The exposition starts by a discussion of molecular similarity and transferability in terms of the underlying electron density, which leads to a qualitative introduction to the quantum theory of atoms in molecules (QTAIM). The starting point of QTAIM is the topological analysis of the molecular electron-density distributions to extract atomic and bond properties that characterize every atom and bond in the molecule. These atomic and bond properties have considerable potential as bases for the construction of robust quantitative structure--activity/property relationships models as shown by selected examples in this review. QTAIM is applicable to the electron density calculated from quantum-chemical calculations and/or that obtained from ultra-high resolution x-ray diffraction experiments followed by nonspherical refinement. Atomic and bond properties are introduced followed by examples of application of each of these two families of descriptors. The review ends with a study whereby the molecular electrostatic potential, uniquely determined by the density, is used in conjunction with atomic properties to elucidate the reasons for the biological similarity of bioisosteres.

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Information processing speed mediates the relationship between white matter and general intelligence in schizophrenia.

PubMed

Alloza, Clara; Cox, Simon R; Duff, Barbara; Semple, Scott I; Bastin, Mark E; Whalley, Heather C; Lawrie, Stephen M

2016-08-30

Several authors have proposed that schizophrenia is the result of impaired connectivity between specific brain regions rather than differences in local brain activity. White matter abnormalities have been suggested as the anatomical substrate for this dysconnectivity hypothesis. Information processing speed may act as a key cognitive resource facilitating higher order cognition by allowing multiple cognitive processes to be simultaneously available. However, there is a lack of established associations between these variables in schizophrenia. We hypothesised that the relationship between white matter and general intelligence would be mediated by processing speed. White matter water diffusion parameters were studied using Tract-based Spatial Statistics and computed within 46 regions-of-interest (ROI). Principal component analysis was conducted on these white matter ROI for fractional anisotropy (FA) and mean diffusivity, and on neurocognitive subtests to extract general factors of white mater structure (gFA, gMD), general intelligence (g) and processing speed (gspeed). There was a positive correlation between g and gFA (r= 0.67, p =0.001) that was partially and significantly mediated by gspeed (56.22% CI: 0.10-0.62). These findings suggest a plausible model of structure-function relations in schizophrenia, whereby white matter structure may provide a neuroanatomical substrate for general intelligence, which is partly supported by speed of information processing. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Relationship between brain plasticity, learning and foraging performance in honey bees.

PubMed

Cabirol, Amélie; Cope, Alex J; Barron, Andrew B; Devaud, Jean-Marc

2018-01-01

Brain structure and learning capacities both vary with experience, but the mechanistic link between them is unclear. Here, we investigated whether experience-dependent variability in learning performance can be explained by neuroplasticity in foraging honey bees. The mushroom bodies (MBs) are a brain center necessary for ambiguous olfactory learning tasks such as reversal learning. Using radio frequency identification technology, we assessed the effects of natural variation in foraging activity, and the age when first foraging, on both performance in reversal learning and on synaptic connectivity in the MBs. We found that reversal learning performance improved at foraging onset and could decline with greater foraging experience. If bees started foraging before the normal age, as a result of a stress applied to the colony, the decline in learning performance with foraging experience was more severe. Analyses of brain structure in the same bees showed that the total number of synaptic boutons at the MB input decreased when bees started foraging, and then increased with greater foraging intensity. At foraging onset MB structure is therefore optimized for bees to update learned information, but optimization of MB connectivity deteriorates with foraging effort. In a computational model of the MBs sparser coding of information at the MB input improved reversal learning performance. We propose, therefore, a plausible mechanistic relationship between experience, neuroplasticity, and cognitive performance in a natural and ecological context.

Structure-activity relationship studies of chalcone leading to 3-hydroxy-4,3',4',5'-tetramethoxychalcone and its analogues as potent nuclear factor kappaB inhibitors and their anticancer activities.

PubMed

Srinivasan, Balasubramanian; Johnson, Thomas E; Lad, Rahul; Xing, Chengguo

2009-11-26

Chalcone is a privileged structure, demonstrating promising anti-inflammatory and anticancer activities. One potential mechanism is to suppress nuclear factor kappa B (NF-kappaB) activation. The structures of chalcone-based NF-kappaB inhibitors vary significantly that there is minimum information about their structure-activity relationships (SAR). This study aims to establish SAR of chalcone-based compounds to NF-kappaB inhibition, to explore the feasibility of developing simple chalcone-based potent NF-kappaB inhibitors, and to evaluate their anticancer activities. Three series of chalcones were synthesized in one to three steps with the key step being aldol condensation. These candidates demonstrated a wide range of NF-kappaB inhibitory activities, some of low micromolar potency, establishing that structural complexity is not required for NF-kappaB inhibition. Lead compounds also demonstrate potent cytotoxicity against lung cancer cells. Their cytotoxicities correlate moderately well with their NF-kappaB inhibitory activities, suggesting that suppressing NF-kappaB activation is likely responsible for at least some of the cytotoxicities. One lead compound effectively inhibits lung tumor growth with no signs of adverse side effects.

Biological activity of antitumoural MGBG: the structural variable.

PubMed

Marques, M P M; Gil, F P S C; Calheiros, R; Battaglia, V; Brunati, A M; Agostinelli, E; Toninello, A

2008-05-01

The present study aims at determining the structure-activity relationships (SAR's) ruling the biological function of MGBG (methylglyoxal bis(guanylhydrazone)), a competitive inhibitor of S-adenosyl-L-methionine decarboxylase displaying anticancer activity, involved in the biosynthesis of the naturally occurring polyamines spermidine and spermine. In order to properly understand its biochemical activity, MGBG's structural preferences at physiological conditions were ascertained, by quantum mechanical (DFT) calculations.

1-Amino-4-hydroxy-9,10-anthraquinone - An analogue of anthracycline anticancer drugs, interacts with DNA and induces apoptosis in human MDA-MB-231 breast adinocarcinoma cells: Evaluation of structure-activity relationship using computational, spectroscopic and biochemical studies.

PubMed

Mondal, Palash; Roy, Sanjay; Loganathan, Gayathri; Mandal, Bitapi; Dharumadurai, Dhanasekaran; Akbarsha, Mohammad A; Sengupta, Partha Sarathi; Chattopadhyay, Shouvik; Guin, Partha Sarathi

2015-12-01

The X-ray diffraction and spectroscopic properties of 1-amino-4-hydroxy-9,10-anthraquinone (1-AHAQ), a simple analogue of anthracycline chemotherapeutic drugs were studied by adopting experimental and computational methods. The optimized geometrical parameters obtained from computational methods were compared with the results of X-ray diffraction analysis and the two were found to be in reasonably good agreement. X-ray diffraction study, Density Functional Theory (DFT) and natural bond orbital (NBO) analysis indicated two types of hydrogen bonds in the molecule. The IR spectra of 1-AHAQ were studied by Vibrational Energy Distribution Analysis (VEDA) using potential energy distribution (PED) analysis. The electronic spectra were studied by TDDFT computation and compared with the experimental results. Experimental and theoretical results corroborated each other to a fair extent. To understand the biological efficacy of 1-AHAQ, it was allowed to interact with calf thymus DNA and human breast adino-carcinoma cell MDA-MB-231. It was found that the molecule induces apoptosis in this adinocarcinoma cell, with little, if any, cytotoxic effect in HBL-100 normal breast epithelial cell.

Theoretical Heterogeneous Catalysis: Scaling Relationships and Computational Catalyst Design.

PubMed

Greeley, Jeffrey

2016-06-07

Scaling relationships are theoretical constructs that relate the binding energies of a wide variety of catalytic intermediates across a range of catalyst surfaces. Such relationships are ultimately derived from bond order conservation principles that were first introduced several decades ago. Through the growing power of computational surface science and catalysis, these concepts and their applications have recently begun to have a major impact in studies of catalytic reactivity and heterogeneous catalyst design. In this review, the detailed theory behind scaling relationships is discussed, and the existence of these relationships for catalytic materials ranging from pure metal to oxide surfaces, for numerous classes of molecules, and for a variety of catalytic surface structures is described. The use of the relationships to understand and elucidate reactivity trends across wide classes of catalytic surfaces and, in some cases, to predict optimal catalysts for certain chemical reactions, is explored. Finally, the observation that, in spite of the tremendous power of scaling relationships, their very existence places limits on the maximum rates that may be obtained for the catalyst classes in question is discussed, and promising strategies are explored to overcome these limitations to usher in a new era of theory-driven catalyst design.

Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network.

PubMed

Petrescu-Prahova, Miruna; Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B; Anderson, Lynda A

2015-08-20

Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level.

Application of neuroanatomical ontologies for neuroimaging data annotation.

PubMed

Turner, Jessica A; Mejino, Jose L V; Brinkley, James F; Detwiler, Landon T; Lee, Hyo Jong; Martone, Maryann E; Rubin, Daniel L

2010-01-01

The annotation of functional neuroimaging results for data sharing and re-use is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are "part of" which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a subpart of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuroanatomical ontology is publicly available as a view of FMA at the Bioportal website. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.

Structure activity relationship study of curcumin analogues toward the amyloid-beta aggregation inhibitor.

PubMed

Endo, Hitoshi; Nikaido, Yuri; Nakadate, Mamiko; Ise, Satomi; Konno, Hiroyuki

2014-12-15

Inhibition of the amyloid β aggregation process could possibly prevent the onset of Alzheimer's disease. In this article, we report a structure-activity relationship study of curcumin analogues for anti amyloid β aggregation activity. Compound 7, the ideal amyloid β aggregation inhibitor in vitro among synthesized curcumin analogues, has not only potent anti amyloid β aggregation effects, but also water solubility more than 160 times that of curcumin. In addition, new approaches to improve water solubility of curcumin-type compounds are proposed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Online Activity Levels Are Related to Caffeine Dependency.

PubMed

Phillips, James G; Landhuis, C Erik; Shepherd, Daniel; Ogeil, Rowan P

2016-05-01

Online activity could serve in the future as behavioral markers of emotional states for computer systems (i.e., affective computing). Hence, this study considered relationships between self-reported stimulant use and online study patterns. Sixty-two undergraduate psychology students estimated their daily caffeine use, and this was related to study patterns as tracked by their use of a Learning Management System (Blackboard). Caffeine dependency was associated with less time spent online, lower rates of file access, and fewer online activities completed. Reduced breadth or depth of processing during work/study could be used as a behavioral marker of stimulant use.

IDEF3 formalization report

NASA Technical Reports Server (NTRS)

Menzel, Christopher; Mayer, Richard J.; Edwards, Douglas D.

1991-01-01

The Process Description Capture Method (IDEF3) is one of several Integrated Computer-Aided Manufacturing (ICAM) DEFinition methods developed by the Air Force to support systems engineering activities, and in particular, to support information systems development. These methods have evolved as a distillation of 'good practice' experience by information system developers and are designed to raise the performance level of the novice practitioner to one comparable with that of an expert. IDEF3 is meant to serve as a knowledge acquisition and requirements definition tool that structures the user's understanding of how a given process, event, or system works around process descriptions. A special purpose graphical language accompanying the method serves to highlight temporal precedence and causality relationships relative to the process or event being described.

SAPIENS: Spreading Activation Processor for Information Encoded in Network Structures. Technical Report No. 296.

ERIC Educational Resources Information Center

Ortony, Andrew; Radin, Dean I.

The product of researchers' efforts to develop a computer processor which distinguishes between relevant and irrelevant information in the database, Spreading Activation Processor for Information Encoded in Network Structures (SAPIENS) exhibits (1) context sensitivity, (2) efficiency, (3) decreasing activation over time, (4) summation of…

Designing for aircraft structural crashworthiness

NASA Technical Reports Server (NTRS)

Thomson, R. G.; Caiafa, C.

1981-01-01

This report describes structural aviation crash dynamics research activities being conducted on general aviation aircraft and transport aircraft. The report includes experimental and analytical correlations of load-limiting subfloor and seat configurations tested dynamically in vertical drop tests and in a horizontal sled deceleration facility. Computer predictions using a finite-element nonlinear computer program, DYCAST, of the acceleration time-histories of these innovative seat and subfloor structures are presented. Proposed application of these computer techniques, and the nonlinear lumped mass computer program KRASH, to transport aircraft crash dynamics is discussed. A proposed FAA full-scale crash test of a fully instrumented radio controlled transport airplane is also described.

Seonah Kim, Ph.D. | NREL

Science.gov Websites

lignocellulosic biomass enzymes Design of new catalysts for vapor phase upgrading of biomass pyrolysis Enzymatic Engineering for Continuous Hydrocarbon Fuel Production (PI) Computational Pyrolysis Consortium Zeolite design Celluase enzyme structure-function relationships to design enhanced cellulose systems Catalyst

Relationship between haemolytic and adjuvant activity and structure of protopanaxadiol-type saponins from the roots of Panax notoginseng.

PubMed

Sun, Hong-Xiang; Qin, Feng; Ye, Yi-Ping

2005-12-01

Four protopanaxadiol-type saponins (PDS), ginsenosides-Rb(1), -Rd, notoginsenosides-K, -R(4) isolated from the roots of Panax notoginseng were evaluated for their haemolytic activities and adjuvant potentials on the cellular and humoral immune responses of ICR mice against ovalbumin (OVA). The effect of the substitution pattern of these PDS on their biological activities was investigated and structure-activity relationships were established. Among four PDS, the ranking of the haemolytic activity was K>R(4)>Rb(1)>Rd (P<0.01 or <0.001). Rd, Rb(1), and K could significantly enhance mitogen- and OVA-induced splenocyte proliferation in the OVA-immunized mice (P<0.001), with the order in terms of stimulation index being Rd>Rb(1)>K>R(4). OVA-specific IgG, IgG1, IgG2a and IgG2b antibody levels in the OVA-immunized mice were significantly enhanced by four PDS. Adjuvant potentials of Rd on antibody responses were higher than those of other three PDS. Meanwhile, Rd also significantly enhanced the production of the Th1 and Th2 cytokines in OVA-immunized mice (P<0.05 or <0.01). The structure-activity relationship studies suggested that the length of sugar side chains at position C-20 and the linkage of glucose moiety at position C-3 of protopanaxadiol could affect the haemolytic and adjuvant activities of PDS. The information about this structure/function relationship might be useful for developing semisynthetic tetracyclic triterpenoid saponin derivatives with immunological adjuvant activity, as well as a reference to the distribution of the functional groups composing the saponin molecule.

Classification of epilepsy types through global network analysis of scalp electroencephalograms

NASA Astrophysics Data System (ADS)

Lee, Uncheol; Kim, Seunghwan; Jung, Ki-Young

2006-04-01

Epilepsy is a dynamic disease in which self-organization and emergent structures occur dynamically at multiple levels of neuronal integration. Therefore, the transient relationship within multichannel electroencephalograms (EEGs) is crucial for understanding epileptic processes. In this paper, we show that the global relationship within multichannel EEGs provides us with more useful information in classifying two different epilepsy types than pairwise relationships such as cross correlation. To demonstrate this, we determine the global network structure within channels of the scalp EEG based on the minimum spanning tree method. The topological dissimilarity of the network structures from different types of temporal lobe epilepsy is described in the form of the divergence rate and is computed for 11 patients with left (LTLE) and right temporal lobe epilepsy (RTLE). We find that patients with LTLE and RTLE exhibit different large scale network structures, which emerge at the epoch immediately before the seizure onset, not in the preceding epochs. Our results suggest that patients with the two different epilepsy types display distinct large scale dynamical networks with characteristic epileptic network structures.

A mechanism-based 3D-QSAR approach for classification and prediction of acetylcholinesterase inhibitory potency of organophosphate and carbamate analogs

NASA Astrophysics Data System (ADS)

Lee, Sehan; Barron, Mace G.

2016-04-01

Organophosphate (OP) and carbamate esters can inhibit acetylcholinesterase (AChE) by binding covalently to a serine residue in the enzyme active site, and their inhibitory potency depends largely on affinity for the enzyme and the reactivity of the ester. Despite this understanding, there has been no mechanism-based in silico approach for classification and prediction of the inhibitory potency of ether OPs or carbamates. This prompted us to develop a three dimensional prediction framework for OPs, carbamates, and their analogs. Inhibitory structures of a compound that can form the covalent bond were identified through analysis of docked conformations of the compound and its metabolites. Inhibitory potencies of the selected structures were then predicted using a previously developed three dimensional quantitative structure-active relationship. This approach was validated with a large number of structurally diverse OP and carbamate compounds encompassing widely used insecticides and structural analogs including OP flame retardants and thio- and dithiocarbamate pesticides. The modeling revealed that: (1) in addition to classical OP metabolic activation, the toxicity of carbamate compounds can be dependent on biotransformation, (2) OP and carbamate analogs such as OP flame retardants and thiocarbamate herbicides can act as AChEI, (3) hydrogen bonds at the oxyanion hole is critical for AChE inhibition through the covalent bond, and (4) π-π interaction with Trp86 is necessary for strong inhibition of AChE. Our combined computation approach provided detailed understanding of the mechanism of action of OP and carbamate compounds and may be useful for screening a diversity of chemical structures for AChE inhibitory potency.

Muscle tension line concept in nasolabial muscle complex--based on 3-dimensional reconstruction of nasolabial muscle fibers.

PubMed

Yin, Ningbei; Wu, Jiajun; Chen, Bo; Song, Tao; Ma, Hengyuan; Zhao, Zhenmin; Wang, Yongqian; Li, Haidong; Wu, Di

2015-03-01

Plastic surgeons have attempted various ways to rebuild the aesthetic subunits of the upper lip in patients with cleft lip with less than perfect results in most cases. We propose that repairing the 3 muscle tension line groups in the nasolabial complex will have improved aesthetic results. Micro-computed tomographic scans were performed on the nasolabial tissues of 5 normal aborted fetuses and used to construct a 3-dimensional model to study the nasolabial muscle complex structure. The micro-computed tomographic (CT) scans showed the close relationship and interaction between the muscle fibers of nasalis, pars peripheralis, levator labii superioris, and pars marginalis. Based on the 2-dimensional images obtained from the micro-computed tomographic scans, we suggest the concept of nasolabial muscle complex and muscle tension line group theory: there is a close relationship among the alar part of the nasalis, depressor septi muscle, orbicularis oris muscle, and levator labii superioris alaeque nasi. The tension line groups are 3 tension line structures in the nasolabial muscle complex that interlock with each other at the intersections and maintain the specific shape and aesthetics of the lip and nose.

Relationships between bat occupancy and habitat and landscape structure along a savanna, woodland, forest gradient in the Missouri Ozarks

Treesearch

Clarissa A. Starbuck; Sybill K. Amelon; Frank R. III Thompson

2015-01-01

Many land-management agencies are restoring savannas and woodlands using prescribed fire and forest thinning, and information is needed on how wildlife species respond to these management activities. Our objectives were to evaluate support for relationships of bat site occupancy with vegetation structure and management and landscape composition and structure across a...

Relationships between chemical structure and rat repellency. II. Compounds screened between 1950 and 1960

USGS Publications Warehouse

Bowles, W.A.; Adomaitis, V.A.; DeWitt, J.B.; Pratt, J.J.

1974-01-01

Over 4,600 compounds, chiefly organic types, were evaluated using both a food acceptance test (Part A) and a barrier penetration bioassay (Part B), to correlate relationships between chemical structure and rodent repellency.These chemicals are indexed and classified according to the functional groups present and to the degree of substitution within their molecular structures. The results of reduction in foot consumption for each compound appraised are calculated and their K values listed in Table I.The repellent activities of the functional groups represented, alone or in combinations, are expressed in Table II by a Functional Group Repellency Index. A ranking of these indices suggests that acyclic and heteroyclic compounds containing tri- or pentavalent nitrogen would be a parent compound of choice for synthesizing novel repellents. Other molecular arrangements, spatial configurations and combinations of functional groups are compared.There were 123 active, interesting or promising compounds included in the 699 having K values of 85 or greater, which were selected for the barrier appraisal study. These chemicals were formulated in selective solvents at several concentrations and applied to burlap. Small foot bags were fashioned using the fabric impregnated with the candidate formulation, and exposed to rodent attack following storage periods of varying intervals. The results of these tests are listed in Table III. Again, those compounds containing nitrogen in the functional groupings indicated a high order of effectiveness. Several commercial patents covering rodent repellents were issued using the data from the food acceptance and barrier studies.Organizations and cooperators which supplied samples for the program are listed in Appendix I. The Wiswesser cipher for compounds in Table I is used in Appendix II to facilitate location of chemicals by sample code number as they appear under the index headings, and for computer storage and analysis.

Relationships between chemical structure and rat repellency: II. compounds screened between 1950 and 1960

USGS Publications Warehouse

Bowles, Walter A.; Adomaitis, V.A.; DeWitt, J.B.; Pratt, J.J.

1974-01-01

Over 4,600 compounds, chiefly organic types, were evaluated using both a food acceptance test (Part A) and a barrier penetration bioassay (Part B), to correlate relationships between chemical structure and rodent repellency. These chemicals are indexed and classified according to the functional groups present and to the degree of substitution within their molecular structures. The results of reduction in food consumption for each compound appraised are calculated and their K values listed in Table 1. The repellent activities of the functional groups represented, alone or in combinations, are expressed in Table II by a Functional Group Repellency Index.. A ranking of these indices suggests that acyclic and heteroyclic compounds containing tri- or pentavalent nitrogen would be a parent compound of choice for synthesizing novel repellents. Other molecular arrangements, spatial configurations and combinations of functional groups are compared. There were 123 active, interesting or promising compounds included in the 699 having K values of 85 or greater, which were selected for the barrier appraisal study. These chemicals were formulated in selective solvents at several concentrations and applied to burlap. Small food bags were fashioned using the fabric impregnated with the candidate formulation, and exposed to rodent attack following storage periods of varying intervals. The results of these tests are listed in Table III. Again, those compounds containing nitrogen in the functional groupings indicated a high order of effectiveness. Several commercial patents covering rodent repellents were issued using the data from the food acceptance and barrier studies. Organizations and cooperators which supplied samples for the program are listed in Appendix I. The Wiswesser cipher for compounds in Table I is used in Appendix II to facilitate location of chemicals by sample code number as they appear under the index headings, and for computer storage and analysis.

Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.

Computation and brain processes, with special reference to neuroendocrine systems.

PubMed

Toni, Roberto; Spaletta, Giulia; Casa, Claudia Della; Ravera, Simone; Sandri, Giorgio

2007-01-01

The development of neural networks and brain automata has made neuroscientists aware that the performance limits of these brain-like devices lies, at least in part, in their computational power. The computational basis of a. standard cybernetic design, in fact, refers to that of a discrete and finite state machine or Turing Machine (TM). In contrast, it has been suggested that a number of human cerebral activites, from feedback controls up to mental processes, rely on a mixing of both finitary, digital-like and infinitary, continuous-like procedures. Therefore, the central nervous system (CNS) of man would exploit a form of computation going beyond that of a TM. This "non conventional" computation has been called hybrid computation. Some basic structures for hybrid brain computation are believed to be the brain computational maps, in which both Turing-like (digital) computation and continuous (analog) forms of calculus might occur. The cerebral cortex and brain stem appears primary candidate for this processing. However, also neuroendocrine structures like the hypothalamus are believed to exhibit hybrid computional processes, and might give rise to computational maps. Current theories on neural activity, including wiring and volume transmission, neuronal group selection and dynamic evolving models of brain automata, bring fuel to the existence of natural hybrid computation, stressing a cooperation between discrete and continuous forms of communication in the CNS. In addition, the recent advent of neuromorphic chips, like those to restore activity in damaged retina and visual cortex, suggests that assumption of a discrete-continuum polarity in designing biocompatible neural circuitries is crucial for their ensuing performance. In these bionic structures, in fact, a correspondence exists between the original anatomical architecture and synthetic wiring of the chip, resulting in a correspondence between natural and cybernetic neural activity. Thus, chip "form" provides a continuum essential to chip "function". We conclude that it is reasonable to predict the existence of hybrid computational processes in the course of many human, brain integrating activities, urging development of cybernetic approaches based on this modelling for adequate reproduction of a variety of cerebral performances.

Structure-Activity Relationships for the Antifungal Activity of Selective Estrogen Receptor Antagonists Related to Tamoxifen

PubMed Central

Butts, Arielle; Martin, Jennifer A.; DiDone, Louis; Bradley, Erin K.; Mutz, Mitchell; Krysan, Damian J.

2015-01-01

Cryptococcosis is one of the most important invasive fungal infections and is a significant contributor to the mortality associated with HIV/AIDS. As part of our program to repurpose molecules related to the selective estrogen receptor modulator (SERM) tamoxifen as anti-cryptococcal agents, we have explored the structure-activity relationships of a set of structurally diverse SERMs and tamoxifen derivatives. Our data provide the first insights into the structural requirements for the antifungal activity of this scaffold. Three key molecular characteristics affecting anti-cryptococcal activity emerged from our studies: 1) the presence of an alkylamino group tethered to one of the aromatic rings of the triphenylethylene core; 2) an appropriately sized aliphatic substituent at the 2 position of the ethylene moiety; and 3) electronegative substituents on the aromatic rings modestly improved activity. Using a cell-based assay of calmodulin antagonism, we found that the anti-cryptococcal activity of the scaffold correlates with calmodulin inhibition. Finally, we developed a homology model of C. neoformans calmodulin and used it to rationalize the structural basis for the activity of these molecules. Taken together, these data and models provide a basis for the further optimization of this promising anti-cryptococcal scaffold. PMID:26016941

Syntheses and anti-MRSA activities of the C3 analogs of mansonone F, a potent anti-bacterial sesquiterpenoid: insights into its structural requirements for anti-MRSA activity.

PubMed

Shin, Dong-Yun; Kim, Sun Nam; Chae, Jung-Hyun; Hyun, Soon-Sil; Seo, Seung-Yong; Lee, Yong-Sil; Lee, Kwang-Ok; Kim, Seok-Ho; Lee, Yun-Sang; Jeong, Jae Min; Choi, Nam-Song; Suh, Young-Ger

2004-09-06

Syntheses and excellent anti-MRSA activities of the mansonone F analogs are reported. In addition, the minimal structural requirements for its anti-MRSA activities as well as its structure-activity relationship including the C3 substituents effects on anti-MRSA activity are also described. In particular, this study revealed that both ortho-quinone and tricyclic systems of mansonone F are essential for anti-MRSA activities.

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-02-01

Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r 2 Pred ) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.

Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

PubMed

Weidlich, Iwona E; Pevzner, Yuri; Miller, Benjamin T; Filippov, Igor V; Woodcock, H Lee; Brooks, Bernard R

2015-01-05

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.

Association between neighborhood socioeconomic status and screen time among pre-school children: a cross-sectional study

PubMed Central

2010-01-01

Background Sedentary behavior is considered a separate construct from physical activity and engaging in sedentary behaviors results in health effects independent of physical activity levels. A major source of sedentary behavior in children is time spent viewing TV or movies, playing video games, and using computers. To date no study has examined the impact of neighborhood socioeconomic status (SES) on pre-school children's screen time behavior. Methods Proxy reports of weekday and weekend screen time (TV/movies, video games, and computer use) were completed by 1633 parents on their 4-5 year-old children in Edmonton, Alberta between November, 2005 and August, 2007. Postal codes were used to classified neighborhoods into low, medium or high SES. Multiple linear and logistic regression models were conducted to examine relationships between screen time and neighborhood SES. Results Girls living in low SES neighborhoods engaged in significantly more weekly overall screen time and TV/movie minutes compared to girls living in high SES neighborhoods. The same relationship was not observed in boys. Children living in low SES neighborhoods were significantly more likely to be video game users and less likely to be computer users compared to children living in high SES neighborhoods. Also, children living in medium SES neighborhoods were significantly less likely to be computer users compared to children living in high SES neighborhoods. Conclusions Some consideration should be given to providing alternative activity opportunities for children, especially girls who live in lower SES neighborhoods. Also, future research should continue to investigate the independent effects of neighborhood SES on screen time as well as the potential mediating variables for this relationship. PMID:20573262

The Dynamic Interplay between Spatialization of Written Units in Writing Activity and Functions of Tools on the Computer

ERIC Educational Resources Information Center

Huh, Joo Hee

2012-01-01

I criticize the typewriting model and linear writing structure of Microsoft Word software for writing in the computer. I problematize bodily movement in writing that the error of the software disregards. In this research, writing activity is viewed as bodily, spatial and mediated activity under the premise of the unity of consciousness and…

Computer methods in designing tourist equipment for people with disabilities

NASA Astrophysics Data System (ADS)

Zuzda, Jolanta GraŻyna; Borkowski, Piotr; Popławska, Justyna; Latosiewicz, Robert; Moska, Eleonora

2017-11-01

Modern technologies enable disabled people to enjoy physical activity every day. Many new structures are matched individually and created for people who fancy active tourism, giving them wider opportunities for active pastime. The process of creating this type of devices in every stage, from initial design through assessment to validation, is assisted by various types of computer support software.

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.

The newly revised interview for deteriorations in daily living activities in dementia (R-IDDD2): distinguishing initiative from performance at assessment.

PubMed

Giebel, Clarissa M; Challis, David; Montaldi, Daniela

2017-03-01

Minimal evidence exists on the detailed deficits in complex instrumental activities of daily living (IADLs) in mild dementia. The aim of this study was twofold, to validate a revised questionnaire focusing measuring the initiative and performance of IADLs in mild dementia and to explore the relationship between individual IADLs and patient and carer well-being. A total of 183 carers of people with mild dementia completed a further modified Revised Interview for Deterioration in Daily Living Activities 2 (R-IDDD2), which comprised new activities such as computer use, as well as sub-activities on the performance scale. Carers also completed questionnaires assessing patient quality of life (QoL-AD), carer quality of life (AC-QoL), and burden (GHQ-12). Persons with dementia were significantly poorer initiating than performing cleaning, doing repair work, and preparing a hot or cold meal, whereas being poorer at performing dressing and following current affairs. Using the computer, preparing a hot meal, finance, and medication management were most impaired, whereas more basic activities of dressing, washing oneself, brushing hair or teeth, and preparing a hot drink were most preserved. Poor initiative and performance on nearly all activities were significantly related to reduced carer and patient well-being. The R-IDDD2 offers a platform to comprehensively assess everyday functioning. Deteriorations in initiative and performance need to be targeted separately in interventions, as the former requires effective triggering and the latter structured training and support. Most activities were significantly associated with well-being, particularly patient quality of life so that improving any activity should improve well-being.

Quantitative studies on structure-DPPH• scavenging activity relationships of food phenolic acids.

PubMed

Jing, Pu; Zhao, Shu-Juan; Jian, Wen-Jie; Qian, Bing-Jun; Dong, Ying; Pang, Jie

2012-11-01

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2(pred) = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties.

Endoperoxide polyketides from a Chinese Plakortis simplex: further evidence of the impact of stereochemistry on antimalarial activity of simple 1,2-dioxanes.

PubMed

Chianese, Giuseppina; Persico, Marco; Yang, Fan; Lin, Hou-Wen; Guo, Yue-Wei; Basilico, Nicoletta; Parapini, Silvia; Taramelli, Donatella; Taglialatela-Scafati, Orazio; Fattorusso, Caterina

2014-09-01

Chemical investigation of the organic extract obtained from the sponge Plakortis simplex collected in the South China Sea afforded five new polyketide endoperoxides (2 and 4-7), along with two known analogues (1 and 3). The stereostructures of these metabolites have been deduced on the basis of spectroscopic analysis and chemical conversion. The isolated endoperoxide derivatives have been tested for their in vitro antimalarial activity against Plasmodium falciparum strains, showing IC50 values in the low micromolar range. The structure-activity relationships were analyzed by means of a detailed computational investigation and rationalized in the light of the mechanism of action proposed for this class of simple antimalarials. The relative orientation of the atoms involved in the putative radical generation and transfer reaction was demonstrated to have a great impact on the antimalarial activity. The resulting 3D pharmacophoric model can be a useful guide to design simple and effective antimalarial lead compounds belonging to the class of 1,2-dioxanes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrated Computational Materials Engineering for Magnesium in Automotive Body Applications

NASA Astrophysics Data System (ADS)

Allison, John E.; Liu, Baicheng; Boyle, Kevin P.; Hector, Lou; McCune, Robert

This paper provides an overview and progress report for an international collaborative project which aims to develop an ICME infrastructure for magnesium for use in automotive body applications. Quantitative processing-micro structure-property relationships are being developed for extruded Mg alloys, sheet-formed Mg alloys and high pressure die cast Mg alloys. These relationships are captured in computational models which are then linked with manufacturing process simulation and used to provide constitutive models for component performance analysis. The long term goal is to capture this information in efficient computational models and in a web-centered knowledge base. The work is being conducted at leading universities, national labs and industrial research facilities in the US, China and Canada. This project is sponsored by the U.S. Department of Energy, the U.S. Automotive Materials Partnership (USAMP), Chinese Ministry of Science and Technology (MOST) and Natural Resources Canada (NRCan).

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

PubMed

Papma, Janne M; Smits, Marion; de Groot, Marius; Mattace Raso, Francesco U; van der Lugt, Aad; Vrooman, Henri A; Niessen, Wiro J; Koudstaal, Peter J; van Swieten, John C; van der Veen, Frederik M; Prins, Niels D

2017-09-01

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

Synthesis-atomic structure-properties relationships in metallic nanoparticles by total scattering experiments and 3D computer simulations: case of Pt-Ru nanoalloy catalysts

NASA Astrophysics Data System (ADS)

Prasai, Binay; Ren, Yang; Shan, Shiyao; Zhao, Yinguang; Cronk, Hannah; Luo, Jin; Zhong, Chuan-Jian; Petkov, Valeri

2015-04-01

An approach to determining the 3D atomic structure of metallic nanoparticles (NPs) in fine detail and using the unique knowledge obtained for rationalizing their synthesis and properties targeted for optimization is described and exemplified on Pt-Ru alloy NPs of importance to the development of devices for clean energy conversion such as fuel cells. In particular, PtxRu100-x alloy NPs, where x = 31, 49 and 75, are synthesized by wet chemistry and activated catalytically by a post-synthesis treatment involving heating under controlled N2-H2 atmosphere. So-activated NPs are evaluated as catalysts for gas-phase CO oxidation and ethanol electro-oxidation reactions taking place in fuel cells. Both as-synthesized and activated NPs are characterized structurally by total scattering experiments involving high-energy synchrotron X-ray diffraction coupled to atomic pair distribution functions (PDFs) analysis. 3D structure models both for as-synthesized and activated NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modelling Sutton-Chen method. Models are refined against the experimental PDF data by reverse Monte Carlo simulations and analysed in terms of prime structural characteristics such as metal-to-metal bond lengths, bond angles and first coordination numbers for Pt and Ru atoms. Analysis indicates that, though of a similar type, the atomic structure of as-synthesized and respective activated NPs differ in several details of importance to NP catalytic properties. Structural characteristics of activated NPs and data for their catalytic activity are compared side by side and strong evidence found that electronic effects, indicated by significant changes in Pt-Pt and Ru-Ru metal bond lengths at NP surface, and practically unrecognized so far atomic ensemble effects, indicated by distinct stacking of atomic layers near NP surface and prevalence of particular configurations of Pt and Ru atoms in these layers, contribute to the observed enhancement of the catalytic activity of PtxRu100-x alloy NPs at x ~ 50. Implications of so-established relationships between the atomic structure and catalytic activity of Pt-Ru alloy NPs on efforts aimed at improving further the latter by tuning-up the former are discussed and the usefulness of detailed NP structure studies to advancing science and technology of metallic NPs - exemplified.An approach to determining the 3D atomic structure of metallic nanoparticles (NPs) in fine detail and using the unique knowledge obtained for rationalizing their synthesis and properties targeted for optimization is described and exemplified on Pt-Ru alloy NPs of importance to the development of devices for clean energy conversion such as fuel cells. In particular, PtxRu100-x alloy NPs, where x = 31, 49 and 75, are synthesized by wet chemistry and activated catalytically by a post-synthesis treatment involving heating under controlled N2-H2 atmosphere. So-activated NPs are evaluated as catalysts for gas-phase CO oxidation and ethanol electro-oxidation reactions taking place in fuel cells. Both as-synthesized and activated NPs are characterized structurally by total scattering experiments involving high-energy synchrotron X-ray diffraction coupled to atomic pair distribution functions (PDFs) analysis. 3D structure models both for as-synthesized and activated NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modelling Sutton-Chen method. Models are refined against the experimental PDF data by reverse Monte Carlo simulations and analysed in terms of prime structural characteristics such as metal-to-metal bond lengths, bond angles and first coordination numbers for Pt and Ru atoms. Analysis indicates that, though of a similar type, the atomic structure of as-synthesized and respective activated NPs differ in several details of importance to NP catalytic properties. Structural characteristics of activated NPs and data for their catalytic activity are compared side by side and strong evidence found that electronic effects, indicated by significant changes in Pt-Pt and Ru-Ru metal bond lengths at NP surface, and practically unrecognized so far atomic ensemble effects, indicated by distinct stacking of atomic layers near NP surface and prevalence of particular configurations of Pt and Ru atoms in these layers, contribute to the observed enhancement of the catalytic activity of PtxRu100-x alloy NPs at x ~ 50. Implications of so-established relationships between the atomic structure and catalytic activity of Pt-Ru alloy NPs on efforts aimed at improving further the latter by tuning-up the former are discussed and the usefulness of detailed NP structure studies to advancing science and technology of metallic NPs - exemplified. Electronic supplementary information (ESI) available: XRD patterns, TEM and 3D structure modelling methodology. See DOI: 10.1039/c5nr00800j

Simulated Screens of DNA Encoded Libraries: The Potential Influence of Chemical Synthesis Fidelity on Interpretation of Structure-Activity Relationships.

PubMed

Satz, Alexander L

2016-07-11

Simulated screening of DNA encoded libraries indicates that the presence of truncated byproducts complicates the relationship between library member enrichment and equilibrium association constant (these truncates result from incomplete chemical reactions during library synthesis). Further, simulations indicate that some patterns observed in reported experimental data may result from the presence of truncated byproducts in the library mixture and not structure-activity relationships. Potential experimental methods of minimizing the presence of truncates are assessed via simulation; the relationship between enrichment and equilibrium association constant for libraries of differing purities is investigated. Data aggregation techniques are demonstrated that allow for more accurate analysis of screening results, in particular when the screened library contains significant quantities of truncates.