Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

Science.gov (United States)

Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

2010-06-30

QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but

Towards interoperable and reproducible QSAR analyses: Exchange of datasets

Directory of Open Access Journals (Sweden)

Spjuth Ola

2010-06-01

Full Text Available Abstract Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join

Sigma-2 receptor ligands QSAR model dataset

Directory of Open Access Journals (Sweden)

Antonio Rescifina

2017-08-01

Full Text Available The data have been obtained from the Sigma-2 Receptor Selective Ligands Database (S2RSLDB and refined according to the QSAR requirements. These data provide information about a set of 548 Sigma-2 (σ2 receptor ligands selective over Sigma-1 (σ1 receptor. The development of the QSAR model has been undertaken with the use of CORAL software using SMILES, molecular graphs and hybrid descriptors (SMILES and graph together. Data here reported include the regression for σ2 receptor pKi QSAR models. The QSAR model was also employed to predict the σ2 receptor pKi values of the FDA approved drugs that are herewith included.

Dynamic analysis of the 7-GeV APS experiment hall foundation based on equivalent lumped parameter modeling

International Nuclear Information System (INIS)

Wambsganss, M.W.

1989-01-01

In this technical note, mass-spring-dashpot, also referred to as equivalent lumped parameter, models are employed to model the soil-foundation interaction of two typical floor segments from the 7-GeV APS experiment hall. Equivalent lumped parameter models have the advantage of being easy to apply and of readily allowing for parameter studies. Analysis requires knowledge of certain properties of the soil including density, shear wave velocity, and Poisson's ratio, as well as knowledge of the degree of homogeneity of the underlying soil stratum. These data for the APS site were determined by a geotechnical investigation. A soil profile and pertinent data, obtained from crosshole seismic testing, are given. Natural frequencies and damping are calculated for the vertical, sliding, rocking, and coupled rocking/sliding modes of vibration. Subsequently, various corrections to account for modeling ''deficiencies'' are considered and their influences evaluated. The equivalent lumped parameter models were developed for machine foundations which, compared with the APS foundation, are smaller in plan dimension. Therefore, the applicability of these models in the analysis of the dynamic characteristics of the APS foundation must be established. The modeling is evaluated by applying the equivalent lumped parameter models in the analysis of large foundations for which test data exists. A comparison of theoretical and test results establishes the basis for an assessment of the applicability and accuracy of the modeling

The Danish (Q)SAR Database Update Project

DEFF Research Database (Denmark)

Nikolov, Nikolai Georgiev; Dybdahl, Marianne; Abildgaard Rosenberg, Sine

2013-01-01

The Danish (Q)SAR Database is a collection of predictions from quantitative structure–activity relationship ((Q)SAR) models for over 70 environmental and human health-related endpoints (covering biodegradation, metabolism, allergy, irritation, endocrine disruption, teratogenicity, mutagenicity......, carcinogenicity and others), each of them available for 185,000 organic substances. The database has been available online since 2005 (http://qsar.food.dtu.dk). A major update project for the Danish (Q)SAR database is under way, with a new online release planned in the beginning of 2015. The updated version...... will contain more than 600,000 discrete organic structures and new, more precise predictions for all endpoints, derived by consensus algorithms from a number of state-of-the-art individual predictions. Copyright © 2013 Published by Elsevier Ireland Ltd....

The applications of PCA in QSAR studies: A case study on CCR5 antagonists.

Science.gov (United States)

Yoo, ChangKyoo; Shahlaei, Mohsen

2018-01-01

Principal component analysis (PCA), as a well-known multivariate data analysis and data reduction technique, is an important and useful algebraic tool in drug design and discovery. PCA, in a typical quantitative structure-activity relationship (QSAR) study, analyzes an original data matrix in which molecules are described by several intercorrelated quantitative dependent variables (molecular descriptors). Although extensively applied, there is disparity in the literature with respect to the applications of PCA in the QSAR studies. This study investigates the different applications of PCA in QSAR studies using a dataset including CCR5 inhibitors. The different types of preprocessing are used to compare the PCA performances. The use of PC plots in the exploratory investigation of matrix of descriptors is described. This work is also proved PCA analysis to be a powerful technique for exploring complex datasets in QSAR studies for identification of outliers. This study shows that PCA is able to easily apply to the pool of calculated structural descriptors and also the extracted information can be used to help decide upon an appropriate harder model for further analysis. © 2017 John Wiley & Sons A/S.

Numerical analysis of the resonance mechanism of the lumped parameter system model for acoustic mine detection

International Nuclear Information System (INIS)

Wang Chi; Zhou Yu-Qiu; Shen Gao-Wei; Wu Wen-Wen; Ding Wei

2013-01-01

The method of numerical analysis is employed to study the resonance mechanism of the lumped parameter system model for acoustic mine detection. Based on the basic principle of the acoustic resonance technique for mine detection and the characteristics of low-frequency acoustics, the ''soil-mine'' system could be equivalent to a damping ''mass-spring'' resonance model with a lumped parameter analysis method. The dynamic simulation software, Adams, is adopted to analyze the lumped parameter system model numerically. The simulated resonance frequency and anti-resonance frequency are 151 Hz and 512 Hz respectively, basically in agreement with the published resonance frequency of 155 Hz and anti-resonance frequency of 513 Hz, which were measured in the experiment. Therefore, the technique of numerical simulation is validated to have the potential for analyzing the acoustic mine detection model quantitatively. The influences of the soil and mine parameters on the resonance characteristics of the soil—mine system could be investigated by changing the parameter setup in a flexible manner. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

The great descriptor melting pot: mixing descriptors for the common good of QSAR models.

Science.gov (United States)

Tseng, Yufeng J; Hopfinger, Anton J; Esposito, Emilio Xavier

2012-01-01

The usefulness and utility of QSAR modeling depends heavily on the ability to estimate the values of molecular descriptors relevant to the endpoints of interest followed by an optimized selection of descriptors to form the best QSAR models from a representative set of the endpoints of interest. The performance of a QSAR model is directly related to its molecular descriptors. QSAR modeling, specifically model construction and optimization, has benefited from its ability to borrow from other unrelated fields, yet the molecular descriptors that form QSAR models have remained basically unchanged in both form and preferred usage. There are many types of endpoints that require multiple classes of descriptors (descriptors that encode 1D through multi-dimensional, 4D and above, content) needed to most fully capture the molecular features and interactions that contribute to the endpoint. The advantages of QSAR models constructed from multiple, and different, descriptor classes have been demonstrated in the exploration of markedly different, and principally biological systems and endpoints. Multiple examples of such QSAR applications using different descriptor sets are described and that examined. The take-home-message is that a major part of the future of QSAR analysis, and its application to modeling biological potency, ADME-Tox properties, general use in virtual screening applications, as well as its expanding use into new fields for building QSPR models, lies in developing strategies that combine and use 1D through nD molecular descriptors.

QSAR Models for Thyroperoxidase Inhibition and Screening of U.S. and EU Chemical Inventories

DEFF Research Database (Denmark)

Abildgaard Rosenberg, Sine; D. Watt, Eric; Judson, Richard S.

2017-01-01

to QSAR1. Of the substances predicted within QSAR2’s applicability domain, 8,790 (19.3%) REACH substances and 7,166 (19.0%) U.S. EPA substances, respectively, were predicted to be TPO inhibitors. A case study on butyl hydroxyanisole (BHA), which is extensively used as an antioxidant, was included.......6% (SD = 4.6%) and 85.3%, respectively. The external validation test set was subsequently merged with the training set to constitute a larger training set totaling 1,519 chemicals for a second model, QSAR2, which underwent robust cross-validation with a balanced accuracy of 82.7% (SD = 2.2%). An analysis...... of QSAR2 identified the ten most discriminating structural features for TPO inhibition and non-inhibition, respectively. Both models were used to screen 72,524 REACH substances and 32,197 U.S. EPA substances, and QSAR2 with the expanded training set had an approximately 10% larger coverages compared...

Comments on lump solutions in SFT

International Nuclear Information System (INIS)

Bonora, Loriano; Tolla, Driba D.

2016-01-01

We analyze a recently proposed scheme to construct analytic lump solutions in open SFT. We argue that in order for the scheme to be operative and to guarantee background independence it must be implemented in the same 2D conformal field theory in which SFT is formulated. We outline and discuss two different possible approaches. Next we reconsider an older proposal for analytic lump solutions and implement a few improvements. In the course of the analysis we formulate a distinction between regular and singular gauge transformations and advocate the necessity of defining a topology in the space of string fields. (orig.)

Comments on lump solutions in SFT

Energy Technology Data Exchange (ETDEWEB)

Bonora, Loriano; Tolla, Driba D. [International School for Advanced Studies (SISSA), Trieste (Italy); INFN, Sezione di Trieste, Trieste (Italy)

2016-04-15

We analyze a recently proposed scheme to construct analytic lump solutions in open SFT. We argue that in order for the scheme to be operative and to guarantee background independence it must be implemented in the same 2D conformal field theory in which SFT is formulated. We outline and discuss two different possible approaches. Next we reconsider an older proposal for analytic lump solutions and implement a few improvements. In the course of the analysis we formulate a distinction between regular and singular gauge transformations and advocate the necessity of defining a topology in the space of string fields. (orig.)

Integration of QSAR and in vitro toxicology.

Science.gov (United States)

Barratt, M D

1998-01-01

The principles of quantitative structure-activity relationships (QSAR) are based on the premise that the properties of a chemical are implicit in its molecular structure. Therefore, if a mechanistic hypothesis can be proposed linking a group of related chemicals with a particular toxic end point, the hypothesis can be used to define relevant parameters to establish a QSAR. Ways in which QSAR and in vitro toxicology can complement each other in development of alternatives to live animal experiments are described and illustrated by examples from acute toxicological end points. Integration of QSAR and in vitro methods is examined in the context of assessing mechanistic competence and improving the design of in vitro assays and the development of prediction models. The nature of biological variability is explored together with its implications for the selection of sets of chemicals for test development, optimization, and validation. Methods are described to support the use of data from in vivo tests that do not meet today's stringent requirements of acceptability. Integration of QSAR and in vitro methods into strategic approaches for the replacement, reduction, and refinement of the use of animals is described with examples. PMID:9599692

Benchmarking Variable Selection in QSAR.

Science.gov (United States)

Eklund, Martin; Norinder, Ulf; Boyer, Scott; Carlsson, Lars

2012-02-01

Variable selection is important in QSAR modeling since it can improve model performance and transparency, as well as reduce the computational cost of model fitting and predictions. Which variable selection methods that perform well in QSAR settings is largely unknown. To address this question we, in a total of 1728 benchmarking experiments, rigorously investigated how eight variable selection methods affect the predictive performance and transparency of random forest models fitted to seven QSAR datasets covering different endpoints, descriptors sets, types of response variables, and number of chemical compounds. The results show that univariate variable selection methods are suboptimal and that the number of variables in the benchmarked datasets can be reduced with about 60 % without significant loss in model performance when using multivariate adaptive regression splines MARS and forward selection. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation

Directory of Open Access Journals (Sweden)

Y. Tang

2007-01-01

Full Text Available This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement schemes. Four sensitivity analysis methods were tested: (1 local analysis using parameter estimation software (PEST, (2 regional sensitivity analysis (RSA, (3 analysis of variance (ANOVA, and (4 Sobol's method. The methods' relative efficiencies and effectiveness have been analyzed and compared. These four sensitivity methods were applied to the lumped Sacramento soil moisture accounting model (SAC-SMA coupled with SNOW-17. Results from this study characterize model sensitivities for two medium sized watersheds within the Juniata River Basin in Pennsylvania, USA. Comparative results for the 4 sensitivity methods are presented for a 3-year time series with 1 h, 6 h, and 24 h time intervals. The results of this study show that model parameter sensitivities are heavily impacted by the choice of analysis method as well as the model time interval. Differences between the two adjacent watersheds also suggest strong influences of local physical characteristics on the sensitivity methods' results. This study also contributes a comprehensive assessment of the repeatability, robustness, efficiency, and ease-of-implementation of the four sensitivity methods. Overall ANOVA and Sobol's method were shown to be superior to RSA and PEST. Relative to one another, ANOVA has reduced computational requirements and Sobol's method yielded more robust sensitivity rankings.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

Science.gov (United States)

Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

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

Science.gov (United States)

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

QSAR analysis on Spodoptera litura antifeedant activities for flavone derivatives

International Nuclear Information System (INIS)

Duchowicz, Pablo R.; Goodarzi, Mohammad; Ocsachoque, Marco A.; Romanelli, Gustavo P.; Ortiz, Erlinda del V.; Autino, Juan C.; Bennardi, Daniel O.; Ruiz, Diego M.; Castro, Eduardo A.

2009-01-01

We establish useful models that relate experimentally measured biological activities of compounds to their molecular structure. The pED 50 feeding inhibition on Spodoptera litura species exhibited by aurones, chromones, 3-coumarones and flavones is analyzed in this work through the hypothesis encompassed in the Quantitative Structure-Activity Relationships (QSAR) Theory. This constitutes a first necessary computationally based step during the design of more bio-friendly repellents that could lead to insights for improving the insecticidal activities of the investigated compounds. After optimizing the molecular structure of each furane and pyrane benzoderivative with the semiempirical molecular orbitals method PM3, more than a thousand of constitutional, topological, geometrical and electronic descriptors are calculated and multiparametric linear regression models are established on the antifeedant potencies. The feature selection method employed in this study is the Replacement Method, which has proven to be successful in previous analyzes. We establish the QSAR both for the complete molecular set of compounds and also for each chemical class, so that acceptably describing the variation of the inhibitory activities from the knowledge of their structure and thus achieving useful predictive results. The main interest of developing trustful QSAR models is that these enable the prediction of compounds having no experimentally measured activities for any reason. Therefore, the structure-activity relationships are further employed for investigating the antifeedant activity on previously synthesized 2-,7-substituted benzopyranes, which do not pose any measured values on the biological expression. One of them, 2-(α-naphtyl)-4H-1-benzopyran-4-one, results in a promising structure to be experimentally analyzed as it has predicted pED 50 = 1.162.

Application of QSAR models in analysis of antibacterial activity of some benzimidazole derivatives against Sarcina lutea

Directory of Open Access Journals (Sweden)

Podunavac-Kuzmanović Sanja O.

2013-01-01

Full Text Available In the present paper, a quantitative structure activity relationship (QSAR has been carried out on a series of 2-methyl and 2-aminobenzimidazole derivatives to identify the lipophilicity requirements for their inhibitory activity against bacteria Sarcina lutea. The tested compounds displayed in vitro antibacterial activity and minimum inhibitory concentration (MIC was determined for all compounds. The partition coefficients of the studied compounds were measured by the shake flask method (log P and by theoretical calculation (Clog P. The relationships between lipophilicity descriptors and antibacterial activities were investigated and the mathematical models have been developed as a calibration models for predicting the inhibitory activity of this class of compounds. The models were validated by leave-one-out (LOO technique as well as by the calculation of statistical parameters for the established models. Therefore, QSAR analysis reveals that lipophilicity descriptor govern the inhibitory activity of benzimidazoles studied against Sarcina lutea.

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1.

Science.gov (United States)

Fatima, Sabiha; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2012-08-01

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r², q²(loo) and r²(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r²(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites.

Directory of Open Access Journals (Sweden)

Meric Ataman

2017-07-01

Full Text Available In the post-genomic era, Genome-scale metabolic networks (GEMs have emerged as invaluable tools to understand metabolic capabilities of organisms. Different parts of these metabolic networks are defined as subsystems/pathways, which are sets of functional roles to implement a specific biological process or structural complex, such as glycolysis and TCA cycle. Subsystem/pathway definition is also employed to delineate the biosynthetic routes that produce biomass building blocks. In databases, such as MetaCyc and SEED, these representations are composed of linear routes from precursors to target biomass building blocks. However, this approach cannot capture the nested, complex nature of GEMs. Here we implemented an algorithm, lumpGEM, which generates biosynthetic subnetworks composed of reactions that can synthesize a target metabolite from a set of defined core precursor metabolites. lumpGEM captures balanced subnetworks, which account for the fate of all metabolites along the synthesis routes, thus encapsulating reactions from various subsystems/pathways to balance these metabolites in the metabolic network. Moreover, lumpGEM collapses these subnetworks into elementally balanced lumped reactions that specify the cost of all precursor metabolites and cofactors. It also generates alternative subnetworks and lumped reactions for the same metabolite, accounting for the flexibility of organisms. lumpGEM is applicable to any GEM and any target metabolite defined in the network. Lumped reactions generated by lumpGEM can be also used to generate properly balanced reduced core metabolic models.

Analysis of transient heat conduction in a PWR fuel rod by an improved lumped parameter approach

Energy Technology Data Exchange (ETDEWEB)

Dourado, Eneida Regina G. [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil); Cotta, Renato M. [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Mecanica; Jian, Su, E-mail: eneidadourado@gmail.com, E-mail: sujian@nuclear.ufrj.br, E-mail: cotta@mecanica.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear

2017-07-01

This paper aims to analyze transient heat conduction in a nuclear fuel rod by an improved lumped parameter approach. One-dimensional transient heat conduction is considered, with the circumferential symmetry assumed and the axial conduction neglected. The thermal conductivity and specific heat in the fuel pellet are considered temperature dependent, while the thermophysical properties of the cladding are considered constant. Hermite approximation for integration is used to obtain the average temperature and heat flux in the radial direction. Significant improvement over the classical lumped parameter formulation has been achieved. The proposed model can be also used in dynamic analysis of PWR and nuclear power plant simulators. (author)

Analysis of transient heat conduction in a PWR fuel rod by an improved lumped parameter approach

International Nuclear Information System (INIS)

Dourado, Eneida Regina G.; Cotta, Renato M.; Jian, Su

2017-01-01

This paper aims to analyze transient heat conduction in a nuclear fuel rod by an improved lumped parameter approach. One-dimensional transient heat conduction is considered, with the circumferential symmetry assumed and the axial conduction neglected. The thermal conductivity and specific heat in the fuel pellet are considered temperature dependent, while the thermophysical properties of the cladding are considered constant. Hermite approximation for integration is used to obtain the average temperature and heat flux in the radial direction. Significant improvement over the classical lumped parameter formulation has been achieved. The proposed model can be also used in dynamic analysis of PWR and nuclear power plant simulators. (author)

Improving the applicability of (Q)SARs for percutaneous penetration in regulatory risk assessment.

Science.gov (United States)

Bouwman, T; Cronin, M T D; Bessems, J G M; van de Sandt, J J M

2008-04-01

The new regulatory framework REACH (Registration, Evaluation, and Authorisation of Chemicals) foresees the use of non-testing approaches, such as read-across, chemical categories, structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs). Although information on skin absorption data are not a formal requirement under REACH, data on dermal absorption are an integral part of risk assessment of substances/products to which man is predominantly exposed via the dermal route. In this study, we assess the present applicability of publicly available QSARs on skin absorption for risk assessment purposes. We explicitly did not aim to give scientific judgments on individual QSARs. A total of 33 QSARs selected from the public domain were evaluated using the OECD (Organisation for Economic Co-operation and Development) Principles for the Validation of (Q)SAR Models. Additionally, several pragmatic criteria were formulated to select QSARs that are most suitable for their use in regulatory risk assessment. Based on these criteria, four QSARs were selected. The predictivity of these QSARs was evaluated by comparing their outcomes with experimentally derived skin absorption data (for 62 compounds). The predictivity was low for three of four QSARs, whereas one model gave reasonable predictions. Several suggestions are made to increase the applicability of QSARs for skin absorption for risk assessment purposes.

New free Danish online (Q)SAR predictions database with >600,000 substances

DEFF Research Database (Denmark)

Wedebye, Eva Bay; Dybdahl, Marianne; Reffstrup, Trine Klein

Since 2005 the Danish (Q)SAR Database has been freely available on the Internet. It is a tool that allows single chemical substance profiling and screenings based on predicted hazard information. The database is also included in the OECD (Q)SAR Application Toolbox which is used worldwide...... by regulators and industry. A lot of progress in (Q)SAR model development, application and documentation has been made since the publication in 2005. A new and completely rebuild online (Q)SAR predictions database was therefore published in November 2015 at http://qsar.food.dtu.dk. The number of chemicals...... in the database has been expanded from 185,000 to >600,000. As far as possible all organic single constituent substances that were pre-registered under REACH have been included in the new structure set. The new Danish (Q)SAR Database includes estimates from more than 200 (Q)SARs covering a wide range of hazardous...

Learning from Multiple Classifier Systems: Perspectives for Improving Decision Making of QSAR Models in Medicinal Chemistry.

Science.gov (United States)

Pham-The, Hai; Nam, Nguyen-Hai; Nga, Doan-Viet; Hai, Dang Thanh; Dieguez-Santana, Karel; Marrero-Poncee, Yovani; Castillo-Garit, Juan A; Casanola-Martin, Gerardo M; Le-Thi-Thu, Huong

2018-02-09

Quantitative Structure - Activity Relationship (QSAR) modeling has been widely used in medicinal chemistry and computational toxicology for many years. Today, as the amount of chemicals is increasing dramatically, QSAR methods have become pivotal for the purpose of handling the data, identifying a decision, and gathering useful information from data processing. The advances in this field have paved a way for numerous alternative approaches that require deep mathematics in order to enhance the learning capability of QSAR models. One of these directions is the use of Multiple Classifier Systems (MCSs) that potentially provide a means to exploit the advantages of manifold learning through decomposition frameworks, while improving generalization and predictive performance. In this paper, we presented MCS as a next generation of QSAR modeling techniques and discuss the chance to mining the vast number of models already published in the literature. We systematically revisited the theoretical frameworks of MCS as well as current advances in MCS application for QSAR practice. Furthermore, we illustrated our idea by describing ensemble approaches on modeling histone deacetylase (HDACs) inhibitors. We expect that our analysis would contribute to a better understanding about MCS application and its future perspectives for improving the decision making of QSAR models. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Lumped impulses, discrete displacements and a moving load analysis

NARCIS (Netherlands)

Kok, A.W.M.

1997-01-01

Finite element models are usually presented as relations between lumped forces and discrete displacements. Mostly finite element models are found by the elaboration of the method of the virtual work - which is a special case of the Galerkin's variational principle -. By application of Galerkin's

Employing conformational analysis in the molecular modeling of agrochemicals: insights on QSAR parameters of 2,4-D

Directory of Open Access Journals (Sweden)

Matheus Puggina de Freitas

2013-12-01

Full Text Available A common practice to compute ligand conformations of compounds with various degrees of freedom to be used in molecular modeling (QSAR and docking studies is to perform a conformational distribution based on repeated random sampling, such as Monte-Carlo methods. Further calculations are often required. This short review describes some methods used for conformational analysis and the implications of using selected conformations in QSAR. A case study is developed for 2,4-dichlorophenoxyacetic acid (2,4-D, a widely used herbicide which binds to TIR1 ubiquitin ligase enzyme. The use of such an approach and semi-empirical calculations did not achieve all possible minima for 2,4-D. In addition, the conformations and respective energies obtained by the semi-empirical AM1 method do not match the calculated trends obtained by a high level DFT method. Similar findings were obtained for the carboxylate anion, which is the bioactive form. Finally, the crystal bioactive structure of 2,4-D was not found as a minimum when using Monte-Carlo/AM1 and is similarly populated with another conformer in implicit water solution according to optimization at the B3LYP/aug-cc-pVDZ level. Therefore, quantitative structure-activity relationship (QSAR methods based on three dimensional chemical structures are not fundamental to provide predictive models for 2,4-D congeners as TIR1 ubiquitin ligase ligands, since they do not necessarily reflect the bioactive conformation of this molecule. This probably extends to other systems.

Numerical analysis of macro-crack formation behavior within the lump coke; Cokes sonai kiretsu shinten kiko no kaiseki

Energy Technology Data Exchange (ETDEWEB)

Aoki, H; Sato, H; Miura, T [Tohoku University, Sendai (Japan). Faculty of Engineering

1995-03-15

The thermal stress analysis within lump coke was studied in order to investigate macro-crack formation and deformation behavior which strongly influence heat and mass transfer in a coke oven chamber. The dilatation of plastic layer, heating rate dependence of thermophysical and mechanical properties of coal/coke, creep in the plastic and semi-coke layers, macro-crack propagation and radiative heat transfer within the macro-crack were considered in an analytical model. The macro-crack propagation was determined from the estimated crack tip stress intensity factor, K{sub I}, at the macro-crack tip compared with the plane strain fracture toughness, K{sub IC}, through the unsteady-state calculation. Calculated results on crack formation and deformation behavior of lump coke were in good agreement with experimental observations in a laboratory-scale oven chamber. The analytical model could predict micro-crack formation within the lump coke normal to the heated wall and the coke surface close to the heated wall. 12 refs., 13 figs.

Cytomorphological study of palpable breast lumps

Directory of Open Access Journals (Sweden)

PK Choudhary

2015-09-01

Full Text Available Background: Breast lump is a very common clinical presentation for which fine needle aspiration cytology is often sought for. Because of it’s significant diagnositic value, FNAC has become a routine tool in the evaluation of the nature of the lesion. The objective of this study was to determine the cytomorphological patterns of breast lump in eastern part of Nepal among individuals attending Nobel Medical College. Materials and Methods: This was a retrospective descriptive study done in department of pathology from December 2012 to June 2015. All individuals presenting with breast lumps was included in this study. FNAC was done as per standard procedure and categorized as per United Kingdom National Health Survey Breast Screening Programme (UK-NHS-BSP categories and further also categorized in to neoplastic and non-neolastic categories. Results: We studied 771 cases of breast lumps. Occurrence of breast lump was more common in female (97.4%. Neoplastic lesions accounted for 84.1% of cases out of which benign comprised of 94.6% and malignant comprised of 5.6%. Common benign lesions observed were that of fibroadenona (264 and fibrocystic changes (204. Ductal carcinoma was the most common malignant lesions. All malignant lesions were observed in older age and female sex population.Conclusion: Most of the cases of breast lumps are benign in nature and very few accounted for malignant cases. There is predominance of benign lesions in young age and increased malignancy in older age and female population. 

Towards Global QSAR Model Building for Acute Toxicity: Munro Database Case Study

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Swapnil Chavan

2014-10-01

Full Text Available A series of 436 Munro database chemicals were studied with respect to their corresponding experimental LD50 values to investigate the possibility of establishing a global QSAR model for acute toxicity. Dragon molecular descriptors were used for the QSAR model development and genetic algorithms were used to select descriptors better correlated with toxicity data. Toxic values were discretized in a qualitative class on the basis of the Globally Harmonized Scheme: the 436 chemicals were divided into 3 classes based on their experimental LD50 values: highly toxic, intermediate toxic and low to non-toxic. The k-nearest neighbor (k-NN classification method was calibrated on 25 molecular descriptors and gave a non-error rate (NER equal to 0.66 and 0.57 for internal and external prediction sets, respectively. Even if the classification performances are not optimal, the subsequent analysis of the selected descriptors and their relationship with toxicity levels constitute a step towards the development of a global QSAR model for acute toxicity.

Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges

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Rodolfo S. Simões

2018-02-01

Full Text Available Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR involve the construction of predictive models that relate a set of descriptors of a chemical compound series and its biological activities with respect to one or more targets in the human body. Datasets used to perform QSAR analyses are generally characterized by a small number of samples and this makes them more complex to build accurate predictive models. In this context, transfer and multi-task learning techniques are very suitable since they take information from other QSAR models to the same biological target, reducing efforts and costs for generating new chemical compounds. Therefore, this review will present the main features of transfer and multi-task learning studies, as well as some applications and its potentiality in drug design projects.

An ensemble model of QSAR tools for regulatory risk assessment.

Science.gov (United States)

Pradeep, Prachi; Povinelli, Richard J; White, Shannon; Merrill, Stephen J

2016-01-01

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa ( κ ): 0

Rational Solutions and Lump Solutions of the Potential YTSF Equation

Science.gov (United States)

Sun, Hong-Qian; Chen, Ai-Hua

2017-07-01

By using of the bilinear form, rational solutions and lump solutions of the potential Yu-Toda-Sasa-Fukuyama (YTSF) equation are derived. Dynamics of the fundamental lump solution, n1-order lump solutions, and N-lump solutions are studied for some special cases. We also find some interaction behaviours of solitary waves and one lump of rational solutions.

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica Proposition, validation and analysis of QSAR models

Directory of Open Access Journals (Sweden)

Anderson Coser Gaudio

2001-10-01

Full Text Available The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.

7 CFR 1726.205 - Multiparty lump sum quotations.

Science.gov (United States)

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Multiparty lump sum quotations. 1726.205 Section 1726....205 Multiparty lump sum quotations. The borrower or its engineer must contact a sufficient number of... basis of written lump sum quotations, the borrower will select the supplier or contractor based on the...

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

Science.gov (United States)

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.

Molecular docking, MM/GBSA and 3D-QSAR studies on EGFR ...

Indian Academy of Sciences (India)

Abstract. Epidermal growth factor receptor (EGFR) is the first growth factor receptor proposed as a target ... Information rendered from 3D-QSAR model and sitemap analysis was used to ... skin making it a key target for anti-tumor strategy. ∗.

Lumped-Parameter Models for Windturbine Footings on Layered Ground

DEFF Research Database (Denmark)

Andersen, Lars

The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...

Lump solutions with interaction phenomena in the (2+1)-dimensional Ito equation

Science.gov (United States)

Zou, Li; Yu, Zong-Bing; Tian, Shou-Fu; Feng, Lian-Li; Li, Jin

2018-03-01

In this paper, we consider the (2+1)-dimensional Ito equation, which was introduced by Ito. By considering the Hirota’s bilinear method, and using the positive quadratic function, we obtain some lump solutions of the Ito equation. In order to ensure rational localization and analyticity of these lump solutions, some sufficient and necessary conditions are provided on the parameters that appeared in the solutions. Furthermore, the interaction solutions between lump solutions and the stripe solitons are discussed by combining positive quadratic function with exponential function. Finally, the dynamic properties of these solutions are shown via the way of graphical analysis by selecting appropriate values of the parameters.

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

Science.gov (United States)

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

International Nuclear Information System (INIS)

Chung, K K; Do, D Q

2010-01-01

In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

QSAR modelling using combined simple competitive learning networks and RBF neural networks.

Science.gov (United States)

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

Improved lumped parameter for annular fuel element thermohydraulic analysis

International Nuclear Information System (INIS)

Duarte, Juliana Pacheco; Su, Jian; Alvim, Antonio Carlos Marques

2011-01-01

Annular fuel elements have been intensively studied for the purpose of increasing power density in light water reactors (LWR). This paper presents an improved lumped parameter model for the dynamics of a LWR core with annular fuel elements, composed of three sub-models: the fuel dynamics model, the neutronics model, and the coolant energy balance model. The transient heat conduction in radial direction is analyzed through an improved lumped parameter formulation. The Hermite approximation for integration is used to obtain the average temperature of the fuel and cladding and also to obtain the average heat flux. The volumetric heat generation in fuel rods was obtained with the point kinetics equations with six delayed neutron groups. The equations for average temperature of fuel and cladding are solved along with the point kinetic equations, assuming linear reactivity and coolant temperature in cases of reactivity insertion. The analytical development of the model and the numeric solution of the ordinary differential equation system were obtained by using Mathematica 7.0. The dynamic behaviors for average temperatures of fuel, cladding and coolant in transient events as well as the reactor power were analyzed. (author)

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

International Nuclear Information System (INIS)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir; He Yan; Xu Jianming

2010-01-01

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

Quantitative structure-activity relationship (QSAR) models for polycyclic aromatic hydrocarbons (PAHs) dissipation in rhizosphere based on molecular structure and effect size

Energy Technology Data Exchange (ETDEWEB)

Ma Bin; Chen Huaihai; Xu Minmin; Hayat, Tahir [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); He Yan, E-mail: yhe2006@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China); Xu Jianming, E-mail: jmxu@zju.edu.c [Zhejiang Provincial Key Laboratory of Subtropical Soil and Plant Nutrition, College of Environmental and Natural Resource Sciences, Zhejiang University, Hangzhou 310029 (China)

2010-08-15

Rhizoremediation is a significant form of bioremediation for polycyclic aromatic hydrocarbons (PAHs). This study examined the role of molecular structure in determining the rhizosphere effect on PAHs dissipation. Effect size in meta-analysis was employed as activity dataset for building quantitative structure-activity relationship (QSAR) models and accumulative effect sizes of 16 PAHs were used for validation of these models. Based on the genetic algorithm combined with partial least square regression, models for comprehensive dataset, Poaceae dataset, and Fabaceae dataset were built. The results showed that information indices, calculated as information content of molecules based on the calculation of equivalence classes from the molecular graph, were the most important molecular structural indices for QSAR models of rhizosphere effect on PAHs dissipation. The QSAR model, based on the molecular structure indices and effect size, has potential to be used in studying and predicting the rhizosphere effect of PAHs dissipation. - Effect size based on meta-analysis was used for building PAHs dissipation quantitative structure-activity relationship (QSAR) models.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

Science.gov (United States)

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets.

Science.gov (United States)

Martínez-Santiago, O; Marrero-Ponce, Y; Vivas-Reyes, R; Rivera-Borroto, O M; Hurtado, E; Treto-Suarez, M A; Ramos, Y; Vergara-Murillo, F; Orozco-Ugarriza, M E; Martínez-López, Y

2017-05-01

Graph derivative indices (GDIs) have recently been defined over N-atoms (N = 2, 3 and 4) simultaneously, which are based on the concept of derivatives in discrete mathematics (finite difference), metaphorical to the derivative concept in classical mathematical analysis. These molecular descriptors (MDs) codify topo-chemical and topo-structural information based on the concept of the derivative of a molecular graph with respect to a given event (S) over duplex, triplex and quadruplex relations of atoms (vertices). These GDIs have been successfully applied in the description of physicochemical properties like reactivity, solubility and chemical shift, among others, and in several comparative quantitative structure activity/property relationship (QSAR/QSPR) studies. Although satisfactory results have been obtained in previous modelling studies with the aforementioned indices, it is necessary to develop new, more rigorous analysis to assess the true predictive performance of the novel structure codification. So, in the present paper, an assessment and statistical validation of the performance of these novel approaches in QSAR studies are executed, as well as a comparison with those of other QSAR procedures reported in the literature. To achieve the main aim of this research, QSARs were developed on eight chemical datasets widely used as benchmarks in the evaluation/validation of several QSAR methods and/or many different MDs (fundamentally 3D MDs). Three to seven variable QSAR models were built for each chemical dataset, according to the original dissection into training/test sets. The models were developed by using multiple linear regression (MLR) coupled with a genetic algorithm as the feature wrapper selection technique in the MobyDigs software. Each family of GDIs (for duplex, triplex and quadruplex) behaves similarly in all modelling, although there were some exceptions. However, when all families were used in combination, the results achieved were quantitatively

The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study

Science.gov (United States)

Kuz'min, Victor E.; Muratov, Eugene N.; Artemenko, Anatoly G.; Gorb, Leonid; Qasim, Mohammad; Leszczynski, Jerzy

2008-10-01

The present study applies the Hierarchical Technology for Quantitative Structure-Activity Relationships (HiT QSAR) for (i) evaluation of the influence of the characteristics of 28 nitroaromatic compounds (some of which belong to a widely known class of explosives) as to their toxicity; (ii) prediction of toxicity for new nitroaromatic derivatives; (iii) analysis of the effects of substituents in nitroaromatic compounds on their toxicity in vivo. The 50% lethal dose concentration for rats (LD50) was used to develop the QSAR models based on simplex representation of molecular structure. The preliminary 1D QSAR results show that even the information on the composition of molecules reveals the main tendencies of changes in toxicity. The statistic characteristics for partial least squares 2D QSAR models are quite satisfactory ( R 2 = 0.96-0.98; Q 2 = 0.91-0.93; R 2 test = 0.89-0.92), which allows us to carry out the prediction of activity for 41 novel compounds designed by the application of new combinations of substituents represented in the training set. The comprehensive analysis of toxicity changes as a function of substituent position and nature was carried out. Molecular fragments that promote and interfere with toxicity were defined on the basis of the obtained models. It was shown that the mutual influence of substituents in the benzene ring plays a crucial role regarding toxicity. The influence of different substituents on toxicity can be mediated via different C-H fragments of the aromatic ring.

Lump solutions to the Kadomtsev–Petviashvili equation

Energy Technology Data Exchange (ETDEWEB)

Ma, Wen-Xiu, E-mail: mawx@cas.usf.edu

2015-09-25

Through symbolic computation with Maple, a class of lump solutions, rationally localized in all directions in the space, to the (2 + 1)-dimensional Kadomtsev–Petviashvili (KP) equation is presented, making use of its Hirota bilinear form. The resulting lump solutions contain six free parameters, two of which are due to the translation invariance of the KP equation and the other four of which satisfy a non-zero determinant condition guaranteeing analyticity and rational localization of the solutions. Three contour plots with different determinant values are sequentially made to show that the corresponding lump solution tends to zero when the determinant approaches zero. Two particular lump solutions with specific values of the involved parameters are plotted, as illustrative examples. - Highlights: • Positive quadratic function solutions. • Solitons rationally-localized in all directions in the space. • Solving systems of nonlinear algebraic equations by symbolic computation with Maple.

4D-QSAR: Perspectives in Drug Design

Directory of Open Access Journals (Sweden)

Carolina H. Andrade

2010-05-01

Full Text Available Drug design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into drug candidates. The quantitative structure–activity relationship (QSAR formalisms are among the most important strategies that can be applied for the successful design new molecules. This review provides a comprehensive review on the evolution and current status of 4D-QSAR, highlighting present challenges and new opportunities in drug design.

Lumped-Parameter Models for Wind-Turbine Footings on Layered Ground

DEFF Research Database (Denmark)

Andersen, Lars; Liingaard, Morten

2007-01-01

The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computational model significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...

3D-QSAR Investigation of Synthetic Antioxidant Chromone Derivatives by Molecular Field Analysis

Directory of Open Access Journals (Sweden)

Jiraporn Ungwitayatorn

2008-02-01

Full Text Available A series of 7-hydroxy, 8-hydroxy and 7,8-dihydroxy synthetic chromone derivatives was evaluated for their DPPH free radical scavenging activities. A training set of 30 synthetic chromone derivatives was subject to three-dimensional quantitative structure-activity relationship (3D-QSAR studies using molecular field analysis (MFA. The substitutional requirements for favorable antioxidant activity were investigated and a predictive model that could be used for the design of novel antioxidants was derived. Regression analysis was carried out using genetic partial least squares (G/PLS method. A highly predictive and statistically significant model was generated. The predictive ability of the developed model was assessed using a test set of 5 compounds (r2pred = 0.924. The analyzed MFA model demonstrated a good fit, having r2 value of 0.868 and crossvalidated coefficient r2cv value of 0.771.

Development of QSAR model for immunomodulatory activity of natural coumarinolignoids

Directory of Open Access Journals (Sweden)

Dharmendra K Yadav

2010-07-01

Full Text Available Dharmendra K Yadav, Abha Meena, Ankit Srivastava, D Chanda, Feroz Khan, SK ChattopadhyayMetabolic and Structural Biology Department, Central Institute of Medicinal and Aromatic Plants, Council of Scientific and Industrial Research, PO-CIMAP, IndiaAbstract: Immunomodulation is the process of alteration in immune response due to foreign intrusion of molecules inside the body. Along with the available drugs, a large number of herbal drugs are promoted in traditional Indian treatments, for their immunomodulating activity. Natural coumarinolignoids isolated from the seeds of Cleome viscose have been recognized as having hepatoprotective action and have recently been tested preclinically for their immunomodulatory activity affecting both cell-mediated and humoral immune response. To explore the immunomodulatory compound from derivatives of coumarinolignoids, a quantitative structure activity relationship (QSAR and molecular docking studies were performed. Theoretical results are in accord with the in vivo experimental data studied on Swiss albino mice. Immunostimulatory activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 99% (R2 = 0.99 and predictive accuracy was 96% (RCV2 = 0.96. QSAR studies indicate that dipole moment, steric energy, amide group count, lambda max (UV-visible, and molar refractivity correlates well with biological activity, while decrease in dipole moment, steric energy, and molar refractivity has negative correlation. Docking studies also showed strong binding affinity to immunomodulatory receptors.Keywords: coumarinolignoids, immunomodulation, docking, QSAR, regression model

Predictive QSAR Models for the Toxicity of Disinfection Byproducts

Directory of Open Access Journals (Sweden)

Litang Qin

2017-10-01

Full Text Available Several hundred disinfection byproducts (DBPs in drinking water have been identified, and are known to have potentially adverse health effects. There are toxicological data gaps for most DBPs, and the predictive method may provide an effective way to address this. The development of an in-silico model of toxicology endpoints of DBPs is rarely studied. The main aim of the present study is to develop predictive quantitative structure–activity relationship (QSAR models for the reactive toxicities of 50 DBPs in the five bioassays of X-Microtox, GSH+, GSH−, DNA+ and DNA−. All-subset regression was used to select the optimal descriptors, and multiple linear-regression models were built. The developed QSAR models for five endpoints satisfied the internal and external validation criteria: coefficient of determination (R2 > 0.7, explained variance in leave-one-out prediction (Q2LOO and in leave-many-out prediction (Q2LMO > 0.6, variance explained in external prediction (Q2F1, Q2F2, and Q2F3 > 0.7, and concordance correlation coefficient (CCC > 0.85. The application domains and the meaning of the selective descriptors for the QSAR models were discussed. The obtained QSAR models can be used in predicting the toxicities of the 50 DBPs.

Predictive QSAR Models for the Toxicity of Disinfection Byproducts.

Science.gov (United States)

Qin, Litang; Zhang, Xin; Chen, Yuhan; Mo, Lingyun; Zeng, Honghu; Liang, Yanpeng

2017-10-09

Several hundred disinfection byproducts (DBPs) in drinking water have been identified, and are known to have potentially adverse health effects. There are toxicological data gaps for most DBPs, and the predictive method may provide an effective way to address this. The development of an in-silico model of toxicology endpoints of DBPs is rarely studied. The main aim of the present study is to develop predictive quantitative structure-activity relationship (QSAR) models for the reactive toxicities of 50 DBPs in the five bioassays of X-Microtox, GSH+, GSH-, DNA+ and DNA-. All-subset regression was used to select the optimal descriptors, and multiple linear-regression models were built. The developed QSAR models for five endpoints satisfied the internal and external validation criteria: coefficient of determination ( R ²) > 0.7, explained variance in leave-one-out prediction ( Q ² LOO ) and in leave-many-out prediction ( Q ² LMO ) > 0.6, variance explained in external prediction ( Q ² F1 , Q ² F2 , and Q ² F3 ) > 0.7, and concordance correlation coefficient ( CCC ) > 0.85. The application domains and the meaning of the selective descriptors for the QSAR models were discussed. The obtained QSAR models can be used in predicting the toxicities of the 50 DBPs.

28 CFR 523.16 - Lump sum awards.

Science.gov (United States)

2010-07-01

... satisfactory performance of an unusually hazardous assignment; (c) An act which protects the lives of staff or... TRANSFER COMPUTATION OF SENTENCE Extra Good Time § 523.16 Lump sum awards. Any staff member may recommend... award is calculated. No seniority is accrued for such awards. Staff may recommend lump sum awards of...

Development of quantitative structure activity relationship (QSAR) model for disinfection byproduct (DBP) research: A review of methods and resources

Energy Technology Data Exchange (ETDEWEB)

Chen, Baiyang, E-mail: poplar_chen@hotmail.com [Harbin Institute of Technology Shenzhen Graduate School, Shenzhen Key Laboratory of Water Resource Utilization and Environmental Pollution Control, Shenzhen 518055 (China); Zhang, Tian [Harbin Institute of Technology Shenzhen Graduate School, Shenzhen Key Laboratory of Water Resource Utilization and Environmental Pollution Control, Shenzhen 518055 (China); Bond, Tom [Department of Civil and Environmental Engineering, Imperial College, London SW7 2AZ (United Kingdom); Gan, Yiqun [Harbin Institute of Technology Shenzhen Graduate School, Shenzhen Key Laboratory of Water Resource Utilization and Environmental Pollution Control, Shenzhen 518055 (China)

2015-12-15

Quantitative structure–activity relationship (QSAR) models are tools for linking chemical activities with molecular structures and compositions. Due to the concern about the proliferating number of disinfection byproducts (DBPs) in water and the associated financial and technical burden, researchers have recently begun to develop QSAR models to investigate the toxicity, formation, property, and removal of DBPs. However, there are no standard procedures or best practices regarding how to develop QSAR models, which potentially limit their wide acceptance. In order to facilitate more frequent use of QSAR models in future DBP research, this article reviews the processes required for QSAR model development, summarizes recent trends in QSAR-DBP studies, and shares some important resources for QSAR development (e.g., free databases and QSAR programs). The paper follows the four steps of QSAR model development, i.e., data collection, descriptor filtration, algorithm selection, and model validation; and finishes by highlighting several research needs. Because QSAR models may have an important role in progressing our understanding of DBP issues, it is hoped that this paper will encourage their future use for this application.

Development of quantitative structure activity relationship (QSAR) model for disinfection byproduct (DBP) research: A review of methods and resources

International Nuclear Information System (INIS)

Chen, Baiyang; Zhang, Tian; Bond, Tom; Gan, Yiqun

2015-01-01

Quantitative structure–activity relationship (QSAR) models are tools for linking chemical activities with molecular structures and compositions. Due to the concern about the proliferating number of disinfection byproducts (DBPs) in water and the associated financial and technical burden, researchers have recently begun to develop QSAR models to investigate the toxicity, formation, property, and removal of DBPs. However, there are no standard procedures or best practices regarding how to develop QSAR models, which potentially limit their wide acceptance. In order to facilitate more frequent use of QSAR models in future DBP research, this article reviews the processes required for QSAR model development, summarizes recent trends in QSAR-DBP studies, and shares some important resources for QSAR development (e.g., free databases and QSAR programs). The paper follows the four steps of QSAR model development, i.e., data collection, descriptor filtration, algorithm selection, and model validation; and finishes by highlighting several research needs. Because QSAR models may have an important role in progressing our understanding of DBP issues, it is hoped that this paper will encourage their future use for this application.

Representing Lumped Markov Chains by Minimal Polynomials over Field GF(q)

Science.gov (United States)

Zakharov, V. M.; Shalagin, S. V.; Eminov, B. F.

2018-05-01

A method has been proposed to represent lumped Markov chains by minimal polynomials over a finite field. The accuracy of representing lumped stochastic matrices, the law of lumped Markov chains depends linearly on the minimum degree of polynomials over field GF(q). The method allows constructing the realizations of lumped Markov chains on linear shift registers with a pre-defined “linear complexity”.

BWR MARK I pressure suppression pool mixing and stratification analysis using GOTHIC lumped parameter modeling methodology

International Nuclear Information System (INIS)

Ozdemir, Ozkan Emre; George, Thomas L.

2015-01-01

As a part of the GOTHIC (GOTHIC incorporates technology developed for the electric power industry under the sponsorship of EPRI.) Fukushima Technical Evaluation project (EPRI, 2014a, b, 2015), GOTHIC (EPRI, 2014c) has been benchmarked against test data for pool stratification (EPRI, 2014a, b, Ozdemir and George, 2013). These tests confirmed GOTHIC’s ability to simulate pool mixing and stratification under a variety of anticipated suppression pool operating conditions. The multidimensional modeling requires long simulation times for events that may occur over a period of hours or days. For these scenarios a lumped model of the pressure suppression chamber is desirable to maintain reasonable simulation times. However, a lumped model for the pool is not able to predict the effects of pool stratification that can influence the overall containment response. The main objective of this work is on the development of a correlation that can be used to estimate pool mixing and stratification effects in a lumped modeling approach. A simplified lumped GOTHIC model that includes a two zone model for the suppression pool with controlled circulation between the upper and lower zones was constructed. A pump and associated flow connections are included to provide mixing between the upper and lower pool volumes. Using numerically generated data from a multidimensional GOTHIC model for the suppression pool, a correlation was developed for the mixing rate between the upper and lower pool volumes in a two-zone, lumped model. The mixing rate depends on the pool subcooling, the steam injection rate and the injection depth

OPERA: A free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints

Science.gov (United States)

Collecting the chemical structures and data for necessary QSAR modeling is facilitated by available public databases and open data. However, QSAR model performance is dependent on the quality of data and modeling methodology used. This study developed robust QSAR models for physi...

A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity.

NARCIS (Netherlands)

Jager, T.; Kooijman, S.A.L.M.

2009-01-01

Quantitative structure-activity relationships (QSARs) for ecotoxicity can be used to fill data gaps and limit toxicity testing on animals. QSAR development may additionally reveal mechanistic information based on observed patterns in the data. However, the use of descriptive summary statistics for

Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

Directory of Open Access Journals (Sweden)

Sharifuddin M. Zain

2011-11-01

Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

Rate constants of hydroxyl radical oxidation of polychlorinated biphenyls in the gas phase: A single−descriptor based QSAR and DFT study

International Nuclear Information System (INIS)

Yang, Zhihui; Luo, Shuang; Wei, Zongsu; Ye, Tiantian; Spinney, Richard; Chen, Dong; Xiao, Ruiyang

2016-01-01

The second‒order rate constants (k) of hydroxyl radical (·OH) with polychlorinated biphenyls (PCBs) in the gas phase are of scientific and regulatory importance for assessing their global distribution and fate in the atmosphere. Due to the limited number of measured k values, there is a need to model the k values for unknown PCBs congeners. In the present study, we developed a quantitative structure–activity relationship (QSAR) model with quantum chemical descriptors using a sequential approach, including correlation analysis, principal component analysis, multi−linear regression, validation, and estimation of applicability domain. The result indicates that the single descriptor, polarizability (α), plays an important role in determining the reactivity with a global standardized function of lnk = −0.054 × α ‒ 19.49 at 298 K. In order to validate the QSAR predicted k values and expand the current k value database for PCBs congeners, an independent method, density functional theory (DFT), was employed to calculate the kinetics and thermodynamics of the gas‒phase ·OH oxidation of 2,4′,5-trichlorobiphenyl (PCB31), 2,2′,4,4′-tetrachlorobiphenyl (PCB47), 2,3,4,5,6-pentachlorobiphenyl (PCB116), 3,3′,4,4′,5,5′-hexachlorobiphenyl (PCB169), and 2,3,3′,4,5,5′,6-heptachlorobiphenyl (PCB192) at 298 K at B3LYP/6–311++G**//B3LYP/6–31 + G** level of theory. The QSAR predicted and DFT calculated k values for ·OH oxidation of these PCB congeners exhibit excellent agreement with the experimental k values, indicating the robustness and predictive power of the single–descriptor based QSAR model we developed. - Highlights: • We developed a single−descriptor based QSAR model for ·OH oxidation of PCBs. • We independently validated the QSAR predicted k values of five PCB congeners with the DFT method. • The QSAR predicted and DFT calculated k for the five PCB congeners exhibit excellent agreement. - We developed a single�

QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

Science.gov (United States)

Toropov, Andrey A; Toropova, Alla P; Puzyn, Tomasz; Benfenati, Emilio; Gini, Giuseppina; Leszczynska, Danuta; Leszczynski, Jerzy

2013-06-01

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to predict various endpoints for various substances. The "classic" QSPR/QSAR analysis is based on the representation of the molecular structure by the molecular graph. However, simplified molecular input-line entry system (SMILES) gradually becomes most popular representation of the molecular structure in the databases available on the Internet. Under such circumstances, the development of molecular descriptors calculated directly from SMILES becomes attractive alternative to "classic" descriptors. The CORAL software (http://www.insilico.eu/coral) is provider of SMILES-based optimal molecular descriptors which are aimed to correlate with various endpoints. We analyzed data set on nanoparticles uptake in PaCa2 pancreatic cancer cells. The data set includes 109 nanoparticles with the same core but different surface modifiers (small organic molecules). The concept of a QSAR as a random event is suggested in opposition to "classic" QSARs which are based on the only one distribution of available data into the training and the validation sets. In other words, five random splits into the "visible" training set and the "invisible" validation set were examined. The SMILES-based optimal descriptors (obtained by the Monte Carlo technique) for these splits are calculated with the CORAL software. The statistical quality of all these models is good. Copyright © 2013 Elsevier Ltd. All rights reserved.

Use of Lump Parameter Codes at SNSA

International Nuclear Information System (INIS)

Muehleisen, A.

2006-01-01

The lump parameter codes are due to the specifics of Slovenian regulation used only in a very limited scope by the SNSA itself. The law requires that most of the analysis needed for regulatory decision making have to be performed by technical support organisations (TSOs). The use of lump parameter codes is therefore limited to the amount needed to maintain necessary technical competence and to support, to a degree, the reasoning for raising new issues and methodologies. SNSA has available its own NPP MELCOR model and uses for its own purposes NPP Krsko RELAP model. RELAP model is also part of the SNSA NPA analyser. Here presented recent uses at SNSA include use of NPA in support of a project, aimed at estimating maturity and uses of CFD codes for regulatory purposes, transition from MELCOR 1.8.3 to 1.8.5 model and its validation, developing MELCOR PAR model and use of NPA for training purposes. NPA use in support of investigation of CFD usability has been in performing lump parameter code calculation against which the CFD results could be compared. The case of SI injection and the following boron distribution in the reactor vessel has been used for this purpose. The comparison showed that for the particular case there is no urgent need for CFD code calculations, nevertheless the project clearly demonstrated wealth of additional information that can be gained by the use of CFD code. As far as MELCOR model is concerned, only transition of the model to the newer code version has been performed and PAR input prepared and tested. Even though there is a feeling at SNSA that some preliminary analysis with it (such as analysis of typical accidents with PARs present and analysis in support of wet cavity modification) would be useful as a support for decision making as well as for simple training purposes we have not been able to perform them due to other priorities and lack of human resources. SNSA is additionally tasked with support to TSOs in their efforts to maintain and

Dependence of QSAR models on the selection of trial descriptor sets: a demonstration using nanotoxicity endpoints of decorated nanotubes.

Science.gov (United States)

Shao, Chi-Yu; Chen, Sing-Zuo; Su, Bo-Han; Tseng, Yufeng J; Esposito, Emilio Xavier; Hopfinger, Anton J

2013-01-28

Little attention has been given to the selection of trial descriptor sets when designing a QSAR analysis even though a great number of descriptor classes, and often a greater number of descriptors within a given class, are now available. This paper reports an effort to explore interrelationships between QSAR models and descriptor sets. Zhou and co-workers (Zhou et al., Nano Lett. 2008, 8 (3), 859-865) designed, synthesized, and tested a combinatorial library of 80 surface modified, that is decorated, multi-walled carbon nanotubes for their composite nanotoxicity using six endpoints all based on a common 0 to 100 activity scale. Each of the six endpoints for the 29 most nanotoxic decorated nanotubes were incorporated as the training set for this study. The study reported here includes trial descriptor sets for all possible combinations of MOE, VolSurf, and 4D-fingerprints (FP) descriptor classes, as well as including and excluding explicit spatial contributions from the nanotube. Optimized QSAR models were constructed from these multiple trial descriptor sets. It was found that (a) both the form and quality of the best QSAR models for each of the endpoints are distinct and (b) some endpoints are quite dependent upon 4D-FP descriptors of the entire nanotube-decorator complex. However, other endpoints yielded equally good models only using decorator descriptors with and without the decorator-only 4D-FP descriptors. Lastly, and most importantly, the quality, significance, and interpretation of a QSAR model were found to be critically dependent on the trial descriptor sets used within a given QSAR endpoint study.

Uncovering and testing the fuzzy clusters based on lumped Markov chain in complex network.

Science.gov (United States)

Jing, Fan; Jianbin, Xie; Jinlong, Wang; Jinshuai, Qu

2013-01-01

Identifying clusters, namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. By means of a lumped Markov chain model of a random walker, we propose two novel ways of inferring the lumped markov transition matrix. Furthermore, some useful results are proposed based on the analysis of the properties of the lumped Markov process. To find the best partition of complex networks, a novel framework including two algorithms for network partition based on the optimal lumped Markovian dynamics is derived to solve this problem. The algorithms are constructed to minimize the objective function under this framework. It is demonstrated by the simulation experiments that our algorithms can efficiently determine the probabilities with which a node belongs to different clusters during the learning process and naturally supports the fuzzy partition. Moreover, they are successfully applied to real-world network, including the social interactions between members of a karate club.

Corrosion Inhibition of Q235A Steel in Acid Medium Using Isatin Derivatives: A Qsar Study

International Nuclear Information System (INIS)

Abdo M Al-Fakih; Madzlan Aziz; Abdo M Al-Fakih; Abdallah, H.H.; Hasmerya Maarof; Rosmahaida Jamaludin; Bishir Usman

2016-01-01

Quantitative Structure-Activity Relationship (QSAR) study was performed on 10 isatin derivatives which were reportedly used as corrosion inhibitors. Dragon software was used to calculate the molecular descriptors. Partial least square (PLS) method was used to run the regression analysis between the descriptors and the corrosion inhibition efficiencies (IE) of the inhibitors. A predictive QSAR model was developed with a correlation coefficient (r 2 cal ) of 0.9676. The model validity was assessed through internal and external validation. The results show that cross-validation regression coefficient (r 2 cv ) and prediction regression coefficient (r 2 pred ) are 0.8163 and 0.9189, respectively. The model was used to predict the IE for ten isatin derivatives. The results confirm a good stability and predictive ability of the model. Dragon-based descriptors provide a very good description of the corrosion inhibition properties of the inhibitors. The results of the QSAR study were found to be consistent with the experimental data. (author)

On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.

Science.gov (United States)

Roy, Kunal; Mitra, Indrani

2011-07-01

Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.

Pembelajaran Seni Tari Kuda Lumping Di Desa Dukuhwaluh Kecamatan Kembaran Kab. Banyumas

OpenAIRE

Daryanto, Daryanto

2011-01-01

The goals this research were to determine: 1). What are the requirements given to prospective players of Kuda Lumping; 2). What material provided and what methods are used in training Kuda Lumping; 3). What is the cost required to conduct training of Kuda Lumping, and from which source. 4). How long does it take to produce players who are ready to perform Kuda Lumping showcased in front of an audience. From the research result shows that: 1. Requirements given to players of Kuda Lumping...

PEMBELAJARAN SENI TARI KUDA LUMPING DI DESA DUKUHWALUH KECAMATAN KEMBARAN KAB. BANYUMAS

OpenAIRE

Daryanto Daryanto

2011-01-01

The goals this research were to determine: 1). What are the requirements given to prospective players of Kuda Lumping; 2). What material provided and what methods are used in training Kuda Lumping; 3). What is the cost required to conduct training of Kuda Lumping, and from which source. 4). How long does it take to produce players who are ready to perform Kuda Lumping showcased in front of an audience. From the research result shows that: 1. Requirements given to players of Kuda Lumping...

Insight into the structural requirement of substituted quinazolinone biphenyl acylsulfonamides derivatives as Angiotensin II AT1 receptor antagonist: 2D and 3D QSAR approach

Directory of Open Access Journals (Sweden)

Mukesh C. Sharma

2014-01-01

Full Text Available A series of 19 molecules substituted quinazolinone biphenyl acylsulfonamides derivatives displaying variable inhibition of Angiotensin II receptor AT1 activity were selected to develop models for establishing 2D and 3D QSAR. The compounds in the selected series were characterized by spatial, molecular and electro topological descriptors using QSAR module of Molecular Design Suite (VLife MDS™ 3.5. The best 2D QSAR model was selected, having correlation coefficient r2 (0.8056 and cross validated squared correlation coefficient q2 (0.6742 with external predictive ability of pred_r2 0.7583 coefficient of correlation of predicted data set (pred_r2se 0.2165. The results obtained from QSAR studies could be used in designing better Ang II activity among the congeners in future. The optimum QSAR model showed that the parameters SsssCHE index, SddCE-index, T_2_Cl_4, and SssNHE-index contributed in the model. 3D QSAR analysis by kNN-molecular field analysis approach developed based on principles of the k-nearest neighbor method combined with Genetic algorithms, stepwise forward variable selection approach; a leave-one-out cross-validated correlation coefficient (q2 of 0.6516 and a non-cross-validated correlation coefficient (r2 of 0.8316 and pred_r2 0.6954 were obtained. Contour maps using this approach showed that steric, electrostatic, and hydrophobic field effects dominantly determine binding affinities. The information rendered by 3D QSAR models may lead to a better understanding of structural requirements of Angiotensin II receptor and can help in the design of novel potent antihypertensive molecules.

Decay of Kadomtsev-Petviashvili lumps in dissipative media

Science.gov (United States)

Clarke, S.; Gorshkov, K.; Grimshaw, R.; Stepanyants, Y.

2018-03-01

The decay of Kadomtsev-Petviashvili lumps is considered for a few typical dissipations-Rayleigh dissipation, Reynolds dissipation, Landau damping, Chezy bottom friction, viscous dissipation in the laminar boundary layer, and radiative losses caused by large-scale dispersion. It is shown that the straight-line motion of lumps is unstable under the influence of dissipation. The lump trajectories are calculated for two most typical models of dissipation-the Rayleigh and Reynolds dissipations. A comparison of analytical results obtained within the framework of asymptotic theory with the direct numerical calculations of the Kadomtsev-Petviashvili equation is presented. Good agreement between the theoretical and numerical results is obtained.

An Analysis of the Effect of the U. S. Marine Corps' Lump Sum Selective Reenlistment Bonus Program on Reenlistment Decisions

National Research Council Canada - National Science Library

Barry, Robert

2001-01-01

... the impact of personal characteristics, civilian pay, unemployment, and the lump sum bonus on reenlistment decisions, Marine retention probabilities under the lump sum payment program are compared...

An approach to the interpretation of backpropagation neural network models in QSAR studies.

Science.gov (United States)

Baskin, I I; Ait, A O; Halberstam, N M; Palyulin, V A; Zefirov, N S

2002-03-01

An approach to the interpretation of backpropagation neural network models for quantitative structure-activity and structure-property relationships (QSAR/QSPR) studies is proposed. The method is based on analyzing the first and second moments of distribution of the values of the first and the second partial derivatives of neural network outputs with respect to inputs calculated at data points. The use of such statistics makes it possible not only to obtain actually the same characteristics as for the case of traditional "interpretable" statistical methods, such as the linear regression analysis, but also to reveal important additional information regarding the non-linear character of QSAR/QSPR relationships. The approach is illustrated by an example of interpreting a backpropagation neural network model for predicting position of the long-wave absorption band of cyane dyes.

Organic Micropollutants Removal from Water by Oxidation and Other Processes:QSAR Models, Decision Support System and Hybrids of Processes

KAUST Repository

Sudhakaran, Sairam

2013-08-01

The presence of organic micropollutants (OMPs) in water is of great environmental concern. OMPs such as endocrine disruptors and certain pharmaceuticals have shown alarming effects on aquatic life. OMPs are included in the priority list of contaminants in several government directorate frameworks. The low levels of OMPs concentration (ng/L to μg/L) force the use of sophisticated analytical instruments. Although, the techniques to detect OMPs are progressing, the focus of current research is only on limited, important OMPs due to the high amount of time, cost and effort involved in analyzing them. Alternatively, quantitative structure activity relationship (QSAR) models help to screen processes and propose appropriate options without considerable experimental effort. QSAR models are well-established in regulatory bodies as a method to screen toxic chemicals. The goal of the present thesis was to develop QSAR models for OMPs removal by oxidation. Apart from the QSAR models, a decision support system (DSS) based on multi-criteria analysis (MCA) involving socio-economic-technical and sustainability aspects was developed. Also, hybrids of different water treatment processes were studied to propose a sustainable water treatment train for OMPs removal. In order to build the QSAR models, the ozone/hydroxyl radical rate constants or percent removals of the OMPs were compiled. Several software packages were used to 5 compute the chemical properties of OMPs and perform statistical analyses. For DSS, MCA was used since it allows the comparison of qualitative (non-monetary, non-metric) and quantitative criteria (e.g., costs). Quadrant plots were developed to study the hybrid of natural and advanced water treatment processes. The QSAR models satisfied both chemical and statistical criteria. The DSS resulted in natural treatment and ozonation as the preferred processes for OMPs removal. The QSAR models can be used as a screening tool for OMPs removal by oxidation. Moreover, the

Lump wood combustion process

Science.gov (United States)

Kubesa, Petr; Horák, Jiří; Branc, Michal; Krpec, Kamil; Hopan, František; Koloničný, Jan; Ochodek, Tadeáš; Drastichová, Vendula; Martiník, Lubomír; Malcho, Milan

2014-08-01

The article deals with the combustion process for lump wood in low-power fireplaces (units to dozens of kW). Such a combustion process is cyclical in its nature, and what combustion facility users are most interested in is the frequency, at which fuel needs to be stoked to the fireplace. The paper defines the basic terms such as burnout curve and burning rate curve, which are closely related to the stocking frequency. The fuel burning rate is directly dependent on the immediate thermal power of the fireplace. This is also related to the temperature achieved in the fireplace, magnitude of flue gas losses and the ability to generate conditions favouring the full burnout of the fuel's combustible component, which, at once ensures the minimum production of combustible pollutants. Another part of the paper describes experiments conducted in traditional fireplaces with a grate, at which well-dried lump wood was combusted.

PEMBELAJARAN SENI TARI KUDA LUMPING DI DESA DUKUHWALUH KECAMATAN KEMBARAN KAB. BANYUMAS

Directory of Open Access Journals (Sweden)

Daryanto Daryanto

2011-03-01

Full Text Available The goals this research were to determine: 1. What are the requirements given to prospective players of Kuda Lumping; 2. What material provided and what methods are used in training Kuda Lumping; 3. What is the cost required to conduct training of Kuda Lumping, and from which source. 4. How long does it take to produce players who are ready to perform Kuda Lumping showcased in front of an audience. From the research result shows that: 1. Requirements given to players of Kuda Lumping (Ebeg, are namely: (1 has Kuda Lumping, (2 can dance in group / compact dance, (3 perform the ritual bathing and diving in rivers and (4 conduct ”Ngasrep” or fasting for 3 (three days without stopping. 2. The practice material was first given to prospective players Kuda Lumping is dance. In practing the dance material, the new dancers were directly guided by the seniors. The method used is by giving examples of dancing by the senior players to prospective players. When giving examples accompanied by gamelan / music, while dancer candidates of Kuda Lumping followed. 3. Fee required for training activities at least IDR 400,000,- (four hundred thousand rupiah. This cost does not include the cost to buy a kuda lumping. Sources of cost comes from the self-help group members of kuda lumping, like dalang ( director of the dance and local people. It means the training and activities of Kuda Lumping, did not receive funding / donations from the government, both the village and district governments. The cost for training activities was used to rent the gamelan, to purchase clothing / costume players, “sesaji”, consumption and honorariums. 4. To train / produce, it take a player at least 3.5 (three and a half months and a maximum of 7 (seven months. This calculation is based on the starting time of dance exercise, until doing the bath in the river as the last stage. Key Wordsi: Kuda lumping, learning ,ngasrep, ritual of bathe, ritual offerings, wayang,

3D QSAR models built on structure-based alignments of Abl tyrosine kinase inhibitors.

Science.gov (United States)

Falchi, Federico; Manetti, Fabrizio; Carraro, Fabio; Naldini, Antonella; Maga, Giovanni; Crespan, Emmanuele; Schenone, Silvia; Bruno, Olga; Brullo, Chiara; Botta, Maurizio

2009-06-01

Quality QSAR: A combination of docking calculations and a statistical approach toward Abl inhibitors resulted in a 3D QSAR model, the analysis of which led to the identification of ligand portions important for affinity. New compounds designed on the basis of the model were found to have very good affinity for the target, providing further validation of the model itself.The X-ray crystallographic coordinates of the Abl tyrosine kinase domain in its active, inactive, and Src-like inactive conformations were used as targets to simulate the binding mode of a large series of pyrazolo[3,4-d]pyrimidines (known Abl inhibitors) by means of GOLD software. Receptor-based alignments provided by molecular docking calculations were submitted to a GRID-GOLPE protocol to generate 3D QSAR models. Analysis of the results showed that the models based on the inactive and Src-like inactive conformations had very poor statistical parameters, whereas the sole model based on the active conformation of Abl was characterized by significant internal and external predictive ability. Subsequent analysis of GOLPE PLS pseudo-coefficient contour plots of this model gave us a better understanding of the relationships between structure and affinity, providing suggestions for the next optimization process. On the basis of these results, new compounds were designed according to the hydrophobic and hydrogen bond donor and acceptor contours, and were found to have improved enzymatic and cellular activity with respect to parent compounds. Additional biological assays confirmed the important role of the selected compounds as inhibitors of cell proliferation in leukemia cells.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

Science.gov (United States)

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

Statistical molecular design of balanced compound libraries for QSAR modeling.

Science.gov (United States)

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.

QSAR models based on quantum topological molecular similarity.

Science.gov (United States)

Popelier, P L A; Smith, P J

2006-07-01

A new method called quantum topological molecular similarity (QTMS) was fairly recently proposed [J. Chem. Inf. Comp. Sc., 41, 2001, 764] to construct a variety of medicinal, ecological and physical organic QSAR/QSPRs. QTMS method uses quantum chemical topology (QCT) to define electronic descriptors drawn from modern ab initio wave functions of geometry-optimised molecules. It was shown that the current abundance of computing power can be utilised to inject realistic descriptors into QSAR/QSPRs. In this article we study seven datasets of medicinal interest : the dissociation constants (pK(a)) for a set of substituted imidazolines , the pK(a) of imidazoles , the ability of a set of indole derivatives to displace [(3)H] flunitrazepam from binding to bovine cortical membranes , the influenza inhibition constants for a set of benzimidazoles , the interaction constants for a set of amides and the enzyme liver alcohol dehydrogenase , the natriuretic activity of sulphonamide carbonic anhydrase inhibitors and the toxicity of a series of benzyl alcohols. A partial least square analysis in conjunction with a genetic algorithm delivered excellent models. They are also able to highlight the active site, of the ligand or the molecule whose structure determines the activity. The advantages and limitations of QTMS are discussed.

Identification of cytochrome P450 2D6 and 2C9 substrates and inhibitors by QSAR analysis

DEFF Research Database (Denmark)

Jónsdóttir, Svava Ósk; Ringsted, Tine; Nikolov, Nikolai G.

2012-01-01

This paper presents four new QSAR models for CYP2C9 and CYP2D6 substrate recognition and inhibitor identification based on human clinical data. The models were used to screen a large data set of environmental chemicals for CYP activity, and to analyze the frequency of CYP activity among these com......This paper presents four new QSAR models for CYP2C9 and CYP2D6 substrate recognition and inhibitor identification based on human clinical data. The models were used to screen a large data set of environmental chemicals for CYP activity, and to analyze the frequency of CYP activity among...... these compounds. A large fraction of these chemicals were found to be CYP active, and thus potentially capable of affecting human physiology. 20% of the compounds within applicability domain of the models were predicted to be CYP2C9 substrates, and 17% to be inhibitors. The corresponding numbers for CYP2D6 were 9...... of specific CYP activity. An overrepresentation was seen for poly-aromatic hydrocarbons (group of procarcinogens) among CYP2C9 active and mutagenic compounds compared to CYP2C9 inactive and mutagenic compounds. The mutagenicity was predicted with a QSAR model based on Ames in vitro test data....

Application of Mass Lumped Higher Order Finite Elements

International Nuclear Information System (INIS)

J. Chen, H.R. Strauss, S.C. Jardin, W. Park, L.E. Sugiyama, G. Fu, J. Breslau

2005-01-01

There are many interesting phenomena in extended-MHD such as anisotropic transport, mhd, 2-fluid effects stellarator and hot particles. Any one of them challenges numerical analysts, and researchers are seeking for higher order methods, such as higher order finite difference, higher order finite elements and hp/spectral elements. It is true that these methods give more accurate solution than their linear counterparts. However, numerically they are prohibitively expensive. Here we give a successful solution of this conflict by applying mass lumped higher order finite elements. This type of elements not only keep second/third order accuracy but also scale closely to linear elements by doing mass lumping. This is especially true for second order lump elements. Full M3D and anisotropic transport models are studied

Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

Science.gov (United States)

Winkler, David A; Le, Tu C

2017-01-01

Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients.

Science.gov (United States)

Hisaki, Tomoka; Aiba Née Kaneko, Maki; Yamaguchi, Masahiko; Sasa, Hitoshi; Kouzuki, Hirokazu

2015-04-01

Use of laboratory animals for systemic toxicity testing is subject to strong ethical and regulatory constraints, but few alternatives are yet available. One possible approach to predict systemic toxicity of chemicals in the absence of experimental data is quantitative structure-activity relationship (QSAR) analysis. Here, we present QSAR models for prediction of maximum "no observed effect level" (NOEL) for repeated-dose, developmental and reproductive toxicities. NOEL values of 421 chemicals for repeated-dose toxicity, 315 for reproductive toxicity, and 156 for developmental toxicity were collected from Japan Existing Chemical Data Base (JECDB). Descriptors to predict toxicity were selected based on molecular orbital (MO) calculations, and QSAR models employing multiple independent descriptors as the input layer of an artificial neural network (ANN) were constructed to predict NOEL values. Robustness of the models was indicated by the root-mean-square (RMS) errors after 10-fold cross-validation (0.529 for repeated-dose, 0.508 for reproductive, and 0.558 for developmental toxicity). Evaluation of the models in terms of the percentages of predicted NOELs falling within factors of 2, 5 and 10 of the in-vivo-determined NOELs suggested that the model is applicable to both general chemicals and the subset of chemicals listed in International Nomenclature of Cosmetic Ingredients (INCI). Our results indicate that ANN models using in silico parameters have useful predictive performance, and should contribute to integrated risk assessment of systemic toxicity using a weight-of-evidence approach. Availability of predicted NOELs will allow calculation of the margin of safety, as recommended by the Scientific Committee on Consumer Safety (SCCS).

The utility of QSARs in predicting acute fish toxicity of pesticide metabolites: A retrospective validation approach.

Science.gov (United States)

Burden, Natalie; Maynard, Samuel K; Weltje, Lennart; Wheeler, James R

2016-10-01

The European Plant Protection Products Regulation 1107/2009 requires that registrants establish whether pesticide metabolites pose a risk to the environment. Fish acute toxicity assessments may be carried out to this end. Considering the total number of pesticide (re-) registrations, the number of metabolites can be considerable, and therefore this testing could use many vertebrates. EFSA's recent "Guidance on tiered risk assessment for plant protection products for aquatic organisms in edge-of-field surface waters" outlines opportunities to apply non-testing methods, such as Quantitative Structure Activity Relationship (QSAR) models. However, a scientific evidence base is necessary to support the use of QSARs in predicting acute fish toxicity of pesticide metabolites. Widespread application and subsequent regulatory acceptance of such an approach would reduce the numbers of animals used. The work presented here intends to provide this evidence base, by means of retrospective data analysis. Experimental fish LC50 values for 150 metabolites were extracted from the Pesticide Properties Database (http://sitem.herts.ac.uk/aeru/ppdb/en/atoz.htm). QSAR calculations were performed to predict fish acute toxicity values for these metabolites using the US EPA's ECOSAR software. The most conservative predicted LC50 values generated by ECOSAR were compared with experimental LC50 values. There was a significant correlation between predicted and experimental fish LC50 values (Spearman rs = 0.6304, p < 0.0001). For 62% of metabolites assessed, the QSAR predicted values are equal to or lower than their respective experimental values. Refined analysis, taking into account data quality and experimental variation considerations increases the proportion of sufficiently predictive estimates to 91%. For eight of the nine outliers, there are plausible explanation(s) for the disparity between measured and predicted LC50 values. Following detailed consideration of the robustness of

Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line

Directory of Open Access Journals (Sweden)

Yum Eryanti

2016-12-01

Full Text Available The dataset of curcumin derivatives consists of 45 compounds (Table 1 with their anti cancer biological activity (IC50 against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set.

Classification of baseline toxicants for QSAR predictions to replace fish acute toxicity studies.

Science.gov (United States)

Nendza, Monika; Müller, Martin; Wenzel, Andrea

2017-03-22

Fish acute toxicity studies are required for environmental hazard and risk assessment of chemicals by national and international legislations such as REACH, the regulations of plant protection products and biocidal products, or the GHS (globally harmonised system) for classification and labelling of chemicals. Alternative methods like QSARs (quantitative structure-activity relationships) can replace many ecotoxicity tests. However, complete substitution of in vivo animal tests by in silico methods may not be realistic. For the so-called baseline toxicants, it is possible to predict the fish acute toxicity with sufficient accuracy from log K ow and, hence, valid QSARs can replace in vivo testing. In contrast, excess toxicants and chemicals not reliably classified as baseline toxicants require further in silico, in vitro or in vivo assessments. Thus, the critical task is to discriminate between baseline and excess toxicants. For fish acute toxicity, we derived a scheme based on structural alerts and physicochemical property thresholds to classify chemicals as either baseline toxicants (=predictable by QSARs) or as potential excess toxicants (=not predictable by baseline QSARs). The step-wise approach identifies baseline toxicants (true negatives) in a precautionary way to avoid false negative predictions. Therefore, a certain fraction of false positives can be tolerated, i.e. baseline toxicants without specific effects that may be tested instead of predicted. Application of the classification scheme to a new heterogeneous dataset for diverse fish species results in 40% baseline toxicants, 24% excess toxicants and 36% compounds not classified. Thus, we can conclude that replacing about half of the fish acute toxicity tests by QSAR predictions is realistic to be achieved in the short-term. The long-term goals are classification criteria also for further groups of toxicants and to replace as many in vivo fish acute toxicity tests as possible with valid QSAR

DemQSAR: predicting human volume of distribution and clearance of drugs.

Science.gov (United States)

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is

Rigorous theoretical derivation of lumped models to transmission line systems

International Nuclear Information System (INIS)

Zhao Jixiang

2012-01-01

By virtue of the negative electric parameter concept, i.e. negative lumped resistance, inductance, conductance and capacitance (N-RLGC), the lumped equivalent models of transmission line systems, including the circuit model, two-port π-network and T-network, are given. We start from the N-segment-ladder-like equivalent networks composed distributed parameters, and achieve the input impedance in the form of a continued fraction. Utilizing the continued fraction theory, the expressions of input impedance are obtained under three kinds of extreme cases, i.e. the load impedances are equal to zero, infinity and characteristic impedance, respectively. When the number of segment N is limited to infinity, they are transformed to lumped elements. Comparison between the distributed model and lumped model of transmission lines, the expression of tanh γd, which is the key term in the transmission line equations, are obtained by RLGC, furthermore, according to input admittance, admittance matrix and ABCD matrix of transmission lines, the lumped equivalent circuit models, π-networks and T-networks have been given. The models are verified in the frequency and time domain, respectively, showing that the models are accurate and efficient. (semiconductor integrated circuits)

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

2009-01-01

efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...

A Temperature Dependent Lumped-charge Model for Trench FS-IGBT

DEFF Research Database (Denmark)

Duan, Yaoqiang; Kang, Yong; Iannuzzo, Francesco

2018-01-01

Abstract: This paper proposes a temperature dependent lumped-charge model for FS-IGBT. Due to the evolution of the IGBT structure, the existing lumped-charge IGBT model established for NPT-IGBT is not suitable for the simulation of FS-IGBT. This paper extends the lumped-charge IGBT model including...... the field-stop (FS) structure and temperature characteristics. The temperature characteristics of the model are considered for both the bipolar part and unipolar part. In addition, a new PN junction model which can distinguish the collector structure is presented and validated by TCAD simulation. Finally...

14C chronology of the oldest Scandinavian church in use. An AMS/PIXE study of lime lump carbonate in the mortar

International Nuclear Information System (INIS)

Lindroos, Alf; Ranta, Heikki; 14C Dating Laboratory, Department of Physics and Astronomy, University of Aarhus (Denmark))" data-affiliation=" (AMS 14C Dating Laboratory, Department of Physics and Astronomy, University of Aarhus (Denmark))" >Heinemeier, Jan; Lill, Jan-Olof

2014-01-01

Mortar dating was applied to newly revealed, original mortar in the church of Dalby in Scania, southern Sweden which is considered to be the oldest still standing church in Scandinavia. Small white lime lumps were sampled by chipping from the supporting pillars in the interior of the church. Special emphasis was in sampling lime lumps because the church is situated in the Scania limestone area and aggregate limestone contamination was anticipated in the bulk mortars. Earlier studies have, however, shown that lime lumps do not contain aggregate material but only possible limestone rests from incomplete calcination. The sampled material was prepared for radiocarbon AMS dating. The carbonate in the lime lumps was hydrolyzed according to the sequential leaching technique developed for the Århus 14 C laboratory in Denmark. Prior to the hydrolysis the lime lumps were examined for dead-carbon contamination using a stereo microscope and cathodoluminescence. The lime lumps displayed heterogeneous carbonate luminescence. This is, however, common and it was not considered a problem because carbonate growth in changing pH/Eh conditions often leads to changing luminescence colors. Two lumps had little dead carbon contamination and an early second millennium 14 C signature. One lump, however, seemed to be heavily contaminated with dead carbon. Since the sample passed the microscopic screening, the leftovers of the lump was subjected to PIXE analysis and compared with the other two lumps. The well-defined, early 2nd millennium 14 C age of the lime lumps of this particular church is an important contribution to the discussion on stone church chronology in Scandinavia

Application of Biologically-Based Lumping To Investigate the ...

Science.gov (United States)

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. However, investigators have often considered complex mixtures as one lumped entity. Valuable information can be obtained from these experiments, though this simplification provides little insight into the impact of a mixture's chemical composition on toxicologically-relevant metabolic interactions that may occur among its constituents. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically-based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate performance of our PBPK model. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course kinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for the 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 non-target chemicals. Application of this biologic

Quantitative Structure--Activity Relationship (QSAR) for the Oxidation of Trace Organic Contaminants by Sulfate Radical.

Science.gov (United States)

Xiao, Ruiyang; Ye, Tiantian; Wei, Zongsu; Luo, Shuang; Yang, Zhihui; Spinney, Richard

2015-11-17

The sulfate radical anion (SO4•–) based oxidation of trace organic contaminants (TrOCs) has recently received great attention due to its high reactivity and low selectivity. In this study, a meta-analysis was conducted to better understand the role of functional groups on the reactivity between SO4•– and TrOCs. The results indicate that compounds in which electron transfer and addition channels dominate tend to exhibit a faster second-order rate constants (kSO4•–) than that of H–atom abstraction, corroborating the SO4•– reactivity and mechanisms observed in the individual studies. Then, a quantitative structure activity relationship (QSAR) model was developed using a sequential approach with constitutional, geometrical, electrostatic, and quantum chemical descriptors. Two descriptors, ELUMO and EHOMO energy gap (ELUMO–EHOMO) and the ratio of oxygen atoms to carbon atoms (#O:C), were found to mechanistically and statistically affect kSO4•– to a great extent with the standardized QSAR model: ln kSO4•– = 26.8–3.97 × #O:C – 0.746 × (ELUMO–EHOMO). In addition, the correlation analysis indicates that there is no dominant reaction channel for SO4•– reactions with various structurally diverse compounds. Our QSAR model provides a robust predictive tool for estimating emerging micropollutants removal using SO4•– during wastewater treatment processes.

Experimental realization of optical lumped nanocircuits at infrared wavelengths.

Science.gov (United States)

Sun, Yong; Edwards, Brian; Alù, Andrea; Engheta, Nader

2012-01-29

The integration of radiofrequency electronic methodologies on micro- as well as nanoscale platforms is crucial for information processing and data-storage technologies. In electronics, radiofrequency signals are controlled and manipulated by 'lumped' circuit elements, such as resistors, inductors and capacitors. In earlier work, we theoretically proposed that optical nanostructures, when properly designed and judiciously arranged, could behave as nanoscale lumped circuit elements--but at optical frequencies. Here, for the first time we experimentally demonstrate a two-dimensional optical nanocircuit at mid-infrared wavelengths. With the guidance of circuit theory, we design and fabricate arrays of Si3N4 nanorods with specific deep subwavelength cross-sections, quantitatively evaluate their equivalent impedance as lumped circuit elements in the mid-infrared regime, and by Fourier transform infrared spectroscopy show that these nanostructures can indeed function as two-dimensional optical lumped circuit elements. We further show that the connections among nanocircuit elements, in particular whether they are in series or in parallel combination, can be controlled by the polarization of impinging optical signals, realizing the notion of 'stereo-circuitry' in metatronics-metamaterials-inspired optical circuitry.

Determination of gold in lump by the gamma-activation analysis method

International Nuclear Information System (INIS)

Yantsen, V.A.; Ermakov, K.S.

2006-01-01

Full text: In the report the installation is described used in the Central gamma-activation analysis laboratory (CGAAL) for express quantitative determination of gold concentration in large powdered samples. The method of gold contents determination for non-crushed samples (pieces up to 100 mm). The given gamma-activation analysis method is widely used in mining industry, and at researches related with selection of optimal technological circuits designed for sorting the pieces of ore and rock materials. By developing this method it is now possible to create the technological collection of separated pieces by size, large by the amount of samples, imitating various sorts (by gold concentration in them) and types (by elemental composition) ores, and, based on these collection, to compare the efficiencies of various enrichment methods by knowing in advance the concentrations of gold in these lumps being the final sorting products. The Gamma-activation analysis method of large pieces is mainly used as foundation for the x-ray radiometric (XRR) method of pieces separation of gold-bearing ores from the deposits mined by the Navoi mining combine. It allows significant increase in the rate of research and development works on selection of the most reliable separation characteristics. Based on these one can develop optimal technological circuits for ore enrichment with portion sorting methods. (author)

Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges

OpenAIRE

Rodolfo S. Simões; Vinicius G. Maltarollo; Patricia R. Oliveira; Kathia M. Honorio; Kathia M. Honorio

2018-01-01

Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR) involve the construction of predictive models that relate a set of descriptors of a chemical compound series a...

A primer on QSAR/QSPR modeling fundamental concepts

CERN Document Server

Roy, Kunal; Das, Rudra Narayan

2015-01-01

This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and phar...

Axillary silicone lymphadenopathy presenting with a lump and altered sensation in the breast: a case report

Directory of Open Access Journals (Sweden)

Adams Simon T

2009-03-01

Full Text Available Abstract Introduction Silicone lymphadenopathy is a rare but recognised complication of procedures involving the use of silicone. It has a poorly understood mechanism but is thought to occur following the transportation of silicone particles from silicone-containing prostheses to lymph nodes by macrophages. Case presentation We report of a case involving a 35-year-old woman who presented to the breast clinic with a breast lump and altered sensation below her left nipple 5 years after bilateral cosmetic breast augmentations. A small lump was detected inferior to the nipple but clinical examination and initial ultrasound investigation showed both implants to be intact. However, mammography and magnetic resonance imaging of both breasts revealed both intracapsular and extracapsular rupture of the left breast prosthesis. The patient went on to develop a flu-like illness and tender lumps in the left axilla and right mastoid regions. An excision biopsy of the left axillary lesion and replacement of the ruptured implant was performed. Subsequent histological analysis showed that the axillary lump was a lymph node containing large amounts of silicone. Conclusion The exclusion of malignancy remains the priority when dealing with lumps in the breast or axilla. Silicone lymphadenopathy should however be considered as a differential diagnosis in patients in whom silicone prostheses are present.

Molecular determinants of juvenile hormone action as revealed by 3D QSAR analysis in Drosophila.

Directory of Open Access Journals (Sweden)

Denisa Liszeková

Full Text Available BACKGROUND: Postembryonic development, including metamorphosis, of many animals is under control of hormones. In Drosophila and other insects these developmental transitions are regulated by the coordinate action of two principal hormones, the steroid ecdysone and the sesquiterpenoid juvenile hormone (JH. While the mode of ecdysone action is relatively well understood, the molecular mode of JH action remains elusive. METHODOLOGY/PRINCIPAL FINDINGS: To gain more insights into the molecular mechanism of JH action, we have tested the biological activity of 86 structurally diverse JH agonists in Drosophila melanogaster. The results were evaluated using 3D QSAR analyses involving CoMFA and CoMSIA procedures. Using this approach we have generated both computer-aided and species-specific pharmacophore fingerprints of JH and its agonists, which revealed that the most active compounds must possess an electronegative atom (oxygen or nitrogen at both ends of the molecule. When either of these electronegative atoms are replaced by carbon or the distance between them is shorter than 11.5 A or longer than 13.5 A, their biological activity is dramatically decreased. The presence of an electron-deficient moiety in the middle of the JH agonist is also essential for high activity. CONCLUSIONS/SIGNIFICANCE: The information from 3D QSAR provides guidelines and mechanistic scope for identification of steric and electrostatic properties as well as donor and acceptor hydrogen-bonding that are important features of the ligand-binding cavity of a JH target protein. In order to refine the pharmacophore analysis and evaluate the outcomes of the CoMFA and CoMSIA study we used pseudoreceptor modeling software PrGen to generate a putative binding site surrogate that is composed of eight amino acid residues corresponding to the defined molecular interactions.

The role of men in early detection of their spouses' breast lump(s ...

African Journals Online (AJOL)

We aim to determine whether men can be of help in the early detection of lumps in their spouses' breast. 230 questionnaires were administered to married men. The responses were accepted as “yes” or “no. 217 men (94.35%) responded. 195 (89.86%) were aware of breast cancer. 212 ( 97.7%) were either Christians or ...

Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

Science.gov (United States)

Jhin, Changho; Hwang, Keum Taek

2015-01-01

One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

Directory of Open Access Journals (Sweden)

Changho Jhin

Full Text Available One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS applied quantitative structure-activity relationship models (QSAR were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

Characterization of an air jet haptic lump display.

Science.gov (United States)

Bianchi, Matteo; Gwilliam, James C; Degirmenci, Alperen; Okamura, Allison M

2011-01-01

During manual palpation, clinicians rely on distributed tactile information to identify and localize hard lumps embedded in soft tissue. The development of tactile feedback systems to enhance palpation using robot-assisted minimally invasive surgery (RMIS) systems is challenging due to size and weight constraints, motivating a pneumatic actuation strategy. Recently, an air jet approach has been proposed for generating a lump percept. We use this technique to direct a thin stream of air through an aperture directly on the finger pad, which indents the skin in a hemispherical manner, producing a compelling lump percept. We hypothesize that the perceived parameters of the lump (e.g. size and stiffness) can be controlled by jointly adjusting air pressure and the aperture size through which air escapes. In this work, we investigate how these control variables interact to affect perceived pressure on the finger pad. First, we used a capacitive tactile sensor array to measure the effect of aperture size on output pressure, and found that peak output pressure increases with aperture size. Second, we performed a psychophysical experiment for each aperture size to determine the just noticeable difference (JND) of air pressure on the finger pad. Subject-averaged pressure JND values ranged from 19.4-24.7 kPa, with no statistical differences observed between aperture sizes. The aperture-pressure relationship and the pressure JND values will be fundamental for future display control.

Rutting resistance of asphalt mixture with cup lumps modified binder

Science.gov (United States)

Shaffie, E.; Hanif, W. M. M. Wan; Arshad, A. K.; Hashim, W.

2017-11-01

Rutting is the most common pavement distress in pavement structures which occurs mainly due to several factors such as increasing of traffic volume, climatic conditions and also due to construction design errors. This failure reduced the service life of the pavement, reduced driver safety and increase cost of maintenance. Polymer Modified Binder has been observed for a long time in improving asphalt pavement performance. Research shows that the use of polymer in bituminous mix not only improve the resistance to rutting but also increase the life span of the pavement. This research evaluates the physical properties and rutting performance of dense graded Superpave-designed HMA mix. Two different types of dense graded Superpave HMA mix were developed consists of unmodified binder mix (UMB) and cup lumps rubber (liquid form) modified binder mix (CLMB). Natural rubber polymer modified binder was prepared from addition of 8 percent of cup lumps into binder. Results showed that all the mixes passed the Superpave volumetric properties criteria which indicate that these mixtures were good with respect to durability and flexibility. Furthermore, rutting results from APA rutting test was determined to evaluate the performance of these mixtures. The rutting result of CLMB demonstrates better resistance to rutting than those prepared using UMB mix. Addition of cup lumps rubber in asphalt mixture was found to be significant, where the cup lumps rubber has certainly improves the binder properties and enhanced its rutting resistance due to greater elasticity offered by the cup lumps rubber particles. It shows that the use of cup lumps rubber can significantly reduce the rut depth of asphalt mixture by 41% compared to the minimum rut depth obtained for the UMB mix. Therefore, it can be concluded that the cup lumps rubber is suitable to be used as a modifier to modified binder in order to enhance the properties of the binder and thus improves the performance of asphalt mixes.

Integrated QSAR study for inhibitors of Hedgehog Signal Pathway against multiple cell lines:a collaborative filtering method.

Science.gov (United States)

Gao, Jun; Che, Dongsheng; Zheng, Vincent W; Zhu, Ruixin; Liu, Qi

2012-07-31

The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several

Characterization of the pharmacokinetics of gasoline using PBPK modeling with a complex mixtures chemical lumping approach.

Science.gov (United States)

Dennison, James E; Andersen, Melvin E; Yang, Raymond S H

2003-09-01

Gasoline consists of a few toxicologically significant components and a large number of other hydrocarbons in a complex mixture. By using an integrated, physiologically based pharmacokinetic (PBPK) modeling and lumping approach, we have developed a method for characterizing the pharmacokinetics (PKs) of gasoline in rats. The PBPK model tracks selected target components (benzene, toluene, ethylbenzene, o-xylene [BTEX], and n-hexane) and a lumped chemical group representing all nontarget components, with competitive metabolic inhibition between all target compounds and the lumped chemical. PK data was acquired by performing gas uptake PK studies with male F344 rats in a closed chamber. Chamber air samples were analyzed every 10-20 min by gas chromatography/flame ionization detection and all nontarget chemicals were co-integrated. A four-compartment PBPK model with metabolic interactions was constructed using the BTEX, n-hexane, and lumped chemical data. Target chemical kinetic parameters were refined by studies with either the single chemical alone or with all five chemicals together. o-Xylene, at high concentrations, decreased alveolar ventilation, consistent with respiratory irritation. A six-chemical interaction model with the lumped chemical group was used to estimate lumped chemical partitioning and metabolic parameters for a winter blend of gasoline with methyl t-butyl ether and a summer blend without any oxygenate. Computer simulation results from this model matched well with experimental data from single chemical, five-chemical mixture, and the two blends of gasoline. The PBPK model analysis indicated that metabolism of individual components was inhibited up to 27% during the 6-h gas uptake experiments of gasoline exposures.

Validity and validation of expert (Q)SAR systems.

Science.gov (United States)

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

Molecular docking and 3D-QSAR studies on triazolinone and pyridazinone, non-nucleoside inhibitor of HIV-1 reverse transcriptase.

Science.gov (United States)

Sivan, Sree Kanth; Manga, Vijjulatha

2010-06-01

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors of the HIV-1 reverse transcriptase. Recently a series of Triazolinone and Pyridazinone were reported as potent inhibitors of HIV-1 wild type reverse transcriptase. In the present study, docking and 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 31 molecules. Ligands were built and minimized using Tripos force field and applying Gasteiger-Hückel charges. These ligands were docked into protein active site using GLIDE 4.0. The docked poses were analyzed; the best docked poses were selected and aligned. CoMFA and CoMSIA fields were calculated using SYBYL6.9. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the r2 nv, q2 loo and r2 pred values. The CoMFA model provides the most significant correlation of steric and electrostatic fields with biological activities. The CoMSIA model provides a correlation of steric, electrostatic, acceptor and hydrophobic fields with biological activities. The information rendered by 3D QSAR model initiated us to optimize the lead and design new potential inhibitors.

Application of 4D-QSAR Studies to a Series of Raloxifene Analogs and Design of Potential Selective Estrogen Receptor Modulators

Directory of Open Access Journals (Sweden)

Carlos Rangel Rodrigues

2012-06-01

Full Text Available Four-dimensional quantitative structure-activity relationship (4D-QSAR analysis was applied on a series of 54 2-arylbenzothiophene derivatives, synthesized by Grese and coworkers, based on raloxifene (an estrogen receptor-alpha antagonist, and evaluated as ERa ligands and as inhibitors of estrogen-stimulated proliferation of MCF-7 breast cancer cells. The conformations of each analogue, sampled from a molecular dynamics simulation, were placed in a grid cell lattice according to three trial alignments, considering two grid cell sizes (1.0 and 2.0 Å. The QSAR equations, generated by a combined scheme of genetic algorithms (GA and partial least squares (PLS regression, were evaluated by “leave-one-out” cross-validation, using a training set of 41 compounds. External validation was performed using a test set of 13 compounds. The obtained 4D-QSAR models are in agreement with the proposed mechanism of action for raloxifene. This study allowed a quantitative prediction of compounds’ potency and supported the design of new raloxifene analogs.

Using Toxicological Evidence from QSAR Models in Practice

Science.gov (United States)

The new generation of QSAR models provides supporting documentation in addition to the predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances and to review and increase the reliability of toxicity predictions. Thi...

Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

Science.gov (United States)

Chen, Hongming; Carlsson, Lars; Eriksson, Mats; Varkonyi, Peter; Norinder, Ulf; Nilsson, Ingemar

2013-06-24

A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

MEMS 3-DoF gyroscope design, modeling and simulation through equivalent circuit lumped parameter model

International Nuclear Information System (INIS)

Mian, Muhammad Umer; Khir, M. H. Md.; Tang, T. B.; Dennis, John Ojur; Riaz, Kashif; Iqbal, Abid; Bazaz, Shafaat A.

2015-01-01

Pre-fabrication, behavioural and performance analysis with computer aided design (CAD) tools is a common and fabrication cost effective practice. In light of this we present a simulation methodology for a dual-mass oscillator based 3 Degree of Freedom (3-DoF) MEMS gyroscope. 3-DoF Gyroscope is modeled through lumped parameter models using equivalent circuit elements. These equivalent circuits consist of elementary components which are counterpart of their respective mechanical components, used to design and fabricate 3-DoF MEMS gyroscope. Complete designing of equivalent circuit model, mathematical modeling and simulation are being presented in this paper. Behaviors of the equivalent lumped models derived for the proposed device design are simulated in MEMSPRO T-SPICE software. Simulations are carried out with the design specifications following design rules of the MetalMUMPS fabrication process. Drive mass resonant frequencies simulated by this technique are 1.59 kHz and 2.05 kHz respectively, which are close to the resonant frequencies found by the analytical formulation of the gyroscope. The lumped equivalent circuit modeling technique proved to be a time efficient modeling technique for the analysis of complex MEMS devices like 3-DoF gyroscopes. The technique proves to be an alternative approach to the complex and time consuming couple field analysis Finite Element Analysis (FEA) previously used

MEMS 3-DoF gyroscope design, modeling and simulation through equivalent circuit lumped parameter model

Energy Technology Data Exchange (ETDEWEB)

Mian, Muhammad Umer, E-mail: umermian@gmail.com; Khir, M. H. Md.; Tang, T. B. [Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia); Dennis, John Ojur [Department of Fundamental & Applied Sciences, Universiti Teknologi PETRONAS, Tronoh, Perak (Malaysia); Riaz, Kashif; Iqbal, Abid [Faculty of Electronics Engineering, GIK Institute of Engineering Sciences and Technology, Topi, Khyber Pakhtunkhaw (Pakistan); Bazaz, Shafaat A. [Department of Computer Science, Center for Advance Studies in Engineering, Islamabad (Pakistan)

2015-07-22

Pre-fabrication, behavioural and performance analysis with computer aided design (CAD) tools is a common and fabrication cost effective practice. In light of this we present a simulation methodology for a dual-mass oscillator based 3 Degree of Freedom (3-DoF) MEMS gyroscope. 3-DoF Gyroscope is modeled through lumped parameter models using equivalent circuit elements. These equivalent circuits consist of elementary components which are counterpart of their respective mechanical components, used to design and fabricate 3-DoF MEMS gyroscope. Complete designing of equivalent circuit model, mathematical modeling and simulation are being presented in this paper. Behaviors of the equivalent lumped models derived for the proposed device design are simulated in MEMSPRO T-SPICE software. Simulations are carried out with the design specifications following design rules of the MetalMUMPS fabrication process. Drive mass resonant frequencies simulated by this technique are 1.59 kHz and 2.05 kHz respectively, which are close to the resonant frequencies found by the analytical formulation of the gyroscope. The lumped equivalent circuit modeling technique proved to be a time efficient modeling technique for the analysis of complex MEMS devices like 3-DoF gyroscopes. The technique proves to be an alternative approach to the complex and time consuming couple field analysis Finite Element Analysis (FEA) previously used.

Prediction of Acute Mammalian Toxicity Using QSAR Methods: A Case Study of Sulfur Mustard and Its Breakdown Products

Directory of Open Access Journals (Sweden)

John Wheeler

2012-07-01

Full Text Available Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR, has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance’s database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (the LD₅₀ for determining relative toxicity of a number of substances. In general, the smaller the LD₅₀ value, the more toxic the chemical, and the larger the LD₅₀ value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s of interest, during emergency responses, LD₅₀ values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD₅₀ models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD₅₀ values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.

{sup 14}C chronology of the oldest Scandinavian church in use. An AMS/PIXE study of lime lump carbonate in the mortar

Energy Technology Data Exchange (ETDEWEB)

Lindroos, Alf, E-mail: alf.lindroos@abo.fi [Geology and Mineralogy, Department of Natural Sciences, Åbo Akademi University (Finland); Art History, Faculty of Art, Åbo Akademi University (Finland); Ranta, Heikki [Diocese of Lund, Church of Sweden (Sweden); Heinemeier, Jan [AMS " 1" 4C Dating Laboratory, Department of Physics and Astronomy, University of Aarhus (Denmark); Lill, Jan-Olof [Accelerator Laboratory, Turku PET Centre, Åbo Akademi University (Finland)

2014-07-15

Mortar dating was applied to newly revealed, original mortar in the church of Dalby in Scania, southern Sweden which is considered to be the oldest still standing church in Scandinavia. Small white lime lumps were sampled by chipping from the supporting pillars in the interior of the church. Special emphasis was in sampling lime lumps because the church is situated in the Scania limestone area and aggregate limestone contamination was anticipated in the bulk mortars. Earlier studies have, however, shown that lime lumps do not contain aggregate material but only possible limestone rests from incomplete calcination. The sampled material was prepared for radiocarbon AMS dating. The carbonate in the lime lumps was hydrolyzed according to the sequential leaching technique developed for the Århus {sup 14}C laboratory in Denmark. Prior to the hydrolysis the lime lumps were examined for dead-carbon contamination using a stereo microscope and cathodoluminescence. The lime lumps displayed heterogeneous carbonate luminescence. This is, however, common and it was not considered a problem because carbonate growth in changing pH/Eh conditions often leads to changing luminescence colors. Two lumps had little dead carbon contamination and an early second millennium {sup 14}C signature. One lump, however, seemed to be heavily contaminated with dead carbon. Since the sample passed the microscopic screening, the leftovers of the lump was subjected to PIXE analysis and compared with the other two lumps. The well-defined, early 2nd millennium {sup 14}C age of the lime lumps of this particular church is an important contribution to the discussion on stone church chronology in Scandinavia.

Application of lumped-parameter models

DEFF Research Database (Denmark)

Ibsen, Lars Bo; Liingaard, Morten

This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...

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

Directory of Open Access Journals (Sweden)

Nannan Zhou

2015-06-01

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

A lumped-parameter model for cryo-adsorber hydrogen storage tank

Energy Technology Data Exchange (ETDEWEB)

Senthil Kumar, V.; Raghunathan, K. [India Science Lab, General Motors R and D, Creator Building, International Technology Park, Bangalore 560066 (India); Kumar, Sudarshan [Chemical and Environmental Sciences Lab, General Motors R and D, 30500 Mound Road, Warren, MI 48090 (United States)

2009-07-15

One of the primary requirements for commercialization of hydrogen fuel-cell vehicles is the on-board storage of hydrogen in sufficient quantities. On-board storage of hydrogen by adsorption on nano-porous adsorbents at around liquid nitrogen temperatures and moderate pressures is considered viable and competitive with other storage technologies: liquid hydrogen, compressed gas, and metallic or complex hydrides. The four cryo-adsorber fuel tank processes occur over different time scales: refueling over a few minutes, discharge over a few hours, dormancy over a few days, and venting over a few weeks. The slower processes i.e. discharge, dormancy and venting are expected to have negligible temperature gradients within the bed, and hence are amenable to a lumped-parameter analysis. Here we report a quasi-static lumped-parameter model for the cryo-adsorber fuel tank, and discuss the results for these slower processes. We also describe an alternative solution method for dormancy and venting based on the thermodynamic state description. (author)

Lumped transmission line avalanche pulser

Science.gov (United States)

Booth, Rex

1995-01-01

A lumped linear avalanche transistor pulse generator utilizes stacked transistors in parallel within a stage and couples a plurality of said stages, in series with increasing zener diode limited voltages per stage and decreasing balanced capacitance load per stage to yield a high voltage, high and constant current, very short pulse.

Lump Kinetic Analysis of Syngas Composition Effect on Fischer-Tropsch Synthesis over Cobalt and Cobalt-Rhenium Alumina Supported Catalyst

Directory of Open Access Journals (Sweden)

Dewi Tristantini

2016-03-01

Received: 10th November 2015; Revised: 10th February 2016; Accepted: 16th February 2016 How to Cite: Tristantini, D., Suwignjo, R.K. (2016. Lump Kinetic Analysis of Syngas Composition Effect on Fischer-Tropsch Synthesis over Cobalt and Cobalt-Rhenium Alumina Supported Catalyst. Bulletin of Chemical Reaction Engineering & Catalysis, 11 (1: 84-92. (doi:10.9767/bcrec.11.1.424.84-92 Permalink/DOI: http://dx.doi.org/10.9767/bcrec.11.1.424.84-92

Development of Predictive QSAR Models of 4-Thiazolidinones Antitrypanosomal Activity using Modern Machine Learning Algorithms.

Science.gov (United States)

Kryshchyshyn, Anna; Devinyak, Oleg; Kaminskyy, Danylo; Grellier, Philippe; Lesyk, Roman

2017-11-14

This paper presents novel QSAR models for the prediction of antitrypanosomal activity among thiazolidines and related heterocycles. The performance of four machine learning algorithms: Random Forest regression, Stochastic gradient boosting, Multivariate adaptive regression splines and Gaussian processes regression have been studied in order to reach better levels of predictivity. The results for Random Forest and Gaussian processes regression are comparable and outperform other studied methods. The preliminary descriptor selection with Boruta method improved the outcome of machine learning methods. The two novel QSAR-models developed with Random Forest and Gaussian processes regression algorithms have good predictive ability, which was proved by the external evaluation of the test set with corresponding Q 2 ext =0.812 and Q 2 ext =0.830. The obtained models can be used further for in silico screening of virtual libraries in the same chemical domain in order to find new antitrypanosomal agents. Thorough analysis of descriptors influence in the QSAR models and interpretation of their chemical meaning allows to highlight a number of structure-activity relationships. The presence of phenyl rings with electron-withdrawing atoms or groups in para-position, increased number of aromatic rings, high branching but short chains, high HOMO energy, and the introduction of 1-substituted 2-indolyl fragment into the molecular structure have been recognized as trypanocidal activity prerequisites. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

QSARs for Plasma Protein Binding: Source Data and Predictions

Data.gov (United States)

U.S. Environmental Protection Agency — The dataset has all of the information used to create and evaluate 3 independent QSAR models for the fraction of a chemical unbound by plasma protein (Fub) for...

20 CFR 222.44 - Other relationship determinations for lump-sum payments.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Other relationship determinations for lump... THE RAILROAD RETIREMENT ACT FAMILY RELATIONSHIPS Relationship as Parent, Grandchild, Brother or Sister... have the relationships to the employee shown below for lump-sum payment purposes: (a) Grandchildren. A...

An Integrated Lumped Parameter-CFD approach for off-design ejector performance evaluation

International Nuclear Information System (INIS)

Besagni, Giorgio; Mereu, Riccardo; Chiesa, Paolo; Inzoli, Fabio

2015-01-01

Highlights: • We validate a CFD approach for a convergent nozzle ejector using global and local measurement. • We evaluate seven RANS turbulence models for convergent nozzle ejector. • We introduce a lumped parameter model for on-design and off-design ejector performance evaluation. • We analyze the relationship between local flow behavior and lumped parameters of the model. • We discuss how to improve predicting capabilities of the model by variable parameters calibrated on CFD simulations. - Abstract: This paper presents an Integrated Lumped Parameter Model-Computational Fluid-Dynamics approach for off-design ejector performance evaluation. The purpose of this approach is to evaluate the entrainment ratio, for a fixed geometry, in both on-design and off-design operating conditions. The proposed model is based on a Lumped Parameter Model (LPM) with variable ejector component efficiencies provided by CFD simulations. The CFD results are used for developing maps for ejector component efficiencies in a broad range of operating conditions. The ejector component efficiency maps couple the CFD and the LPM techniques for building an Integrated LPM-CFD approach. The proposed approach is demonstrated for a convergent nozzle ejector and the paper is structured in four parts. At first, the CFD approach is validated by global and local data and seven Reynolds Averaged Navier Stokes (RANS) turbulence models are compared: the k–ω SST showed good performance and was selected for the rest of the analysis. At second, a Lumped Parameter Model (LPM) for subsonic ejector is developed and the ejector component efficiencies have been defined. At third, the CFD approach is used to investigate the flow field, to analyze its influence on ejector component efficiencies and to propose efficiency correlations and maps linking ejector component efficiencies and local flow quantities. In the last part, the efficiency maps are embedded into the lumped parameter model, thus creating

Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

Science.gov (United States)

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. Copyright © 2014 Elsevier Inc. All rights reserved.

Dark lump excitations in superfluid Fermi gases

Science.gov (United States)

Xu, Yan-Xia; Duan, Wen-Shan

2012-11-01

We study the linear and nonlinear properties of two-dimensional matter-wave pulses in disk-shaped superfluid Fermi gases. A Kadomtsev—Petviashvili I (KPI) solitary wave has been realized for superfluid Fermi gases in the limited cases of Bardeen—Cooper—Schrieffer (BCS) regime, Bose—Einstein condensate (BEC) regime, and unitarity regime. One-lump solution as well as one-line soliton solutions for the KPI equation are obtained, and two-line soliton solutions with the same amplitude are also studied in the limited cases. The dependence of the lump propagating velocity and the sound speed of two-dimensional superfluid Fermi gases on the interaction parameter are investigated for the limited cases of BEC and unitarity.

Dark lump excitations in superfluid Fermi gases

International Nuclear Information System (INIS)

Xu Yan-Xia; Duan Wen-Shan

2012-01-01

We study the linear and nonlinear properties of two-dimensional matter-wave pulses in disk-shaped superfluid Fermi gases. A Kadomtsev—Petviashvili I (KPI) solitary wave has been realized for superfluid Fermi gases in the limited cases of Bardeen—Cooper—Schrieffer (BCS) regime, Bose—Einstein condensate (BEC) regime, and unitarity regime. One-lump solution as well as one-line soliton solutions for the KPI equation are obtained, and two-line soliton solutions with the same amplitude are also studied in the limited cases. The dependence of the lump propagating velocity and the sound speed of two-dimensional superfluid Fermi gases on the interaction parameter are investigated for the limited cases of BEC and unitarity

Evolution of the international workshops on quantitative structure-activity relationships (QSARs) in environmental toxicology.

Science.gov (United States)

Kaiser, K L E

2007-01-01

This presentation will review the evolution of the workshops from a scientific and personal perspective. From their modest beginning in 1983, the workshops have developed into larger international meetings, regularly held every two years. Their initial focus on the aquatic sphere soon expanded to include properties and effects on atmospheric and terrestrial species, including man. Concurrent with this broadening of their scientific scope, the workshops have become an important forum for the early dissemination of all aspects of qualitative and quantitative structure-activity research in ecotoxicology and human health effects. Over the last few decades, the field of quantitative structure/activity relationships (QSARs) has quickly emerged as a major scientific method in understanding the properties and effects of chemicals on the environment and human health. From substances that only affect cell membranes to those that bind strongly to a specific enzyme, QSARs provides insight into the biological effects and chemical and physical properties of substances. QSARs are useful for delineating the quantitative changes in biological effects resulting from minor but systematic variations of the structure of a compound with a specific mode of action. In addition, more holistic approaches are being devised that result in our ability to predict the effects of structurally unrelated compounds with (potentially) different modes of action. Research in QSAR environmental toxicology has led to many improvements in the manufacturing, use, and disposal of chemicals. Furthermore, it has led to national policies and international agreements, from use restrictions or outright bans of compounds, such as polychlorinated biphenyls (PCBs), mirex, and highly chlorinated pesticides (e.g. DDT, dieldrin) for the protection of avian predators, to alternatives for ozone-depleting compounds, to better waste treatment systems, to more powerful and specific acting drugs. Most of the recent advances

QSAR study of benzimidazole derivatives inhibition on escherichia ...

African Journals Online (AJOL)

The paper describes a quantitative structure-activity relationship (QSAR) study of IC50 values of benzimidazole derivatives on escherichia coli methionine aminopeptidase. The activity of the 32 inhibitors has been estimated by means of multiple linear regression (MLR) and artificial neural network (ANN) techniques.

Synthesis, biological evaluation, QSAR study and molecular docking of novel N-(4-amino carbonylpiperazinyl) (thio)phosphoramide derivatives as cholinesterase inhibitors.

Science.gov (United States)

Gholivand, Khodayar; Ebrahimi Valmoozi, Ali Asghar; Bonsaii, Mahyar

2014-06-01

Novel (thio)phosphoramidate derivatives based on piperidincarboxamide with the general formula of (NH2-C(O)-C5H9N)-P(X=O,S)R1R2 (1-5) and (NH2-C(O)-C5H9N)2-P(O)R (6-9) were synthesized and characterized by (31)P, (13)C, (1)H NMR, IR spectroscopy. Furthermore, the crystal structure of compound (NH2-C(O)-C5H9N)2-P(O)(OC6H5) (6) was investigated. The activities of derivatives on cholinesterases (ChE) were determined using a modified Ellman's method. Also the mixed-type mechanisms of these compounds were evaluated by Lineweaver-Burk plots. Molecular docking and quantitative structure-activity relationship (QSAR) were used to understand the relationship between molecular structural features and anti-ChE activity, and to predict the binding affinity of phosphoramido-piperidinecarboxamides (PAPCAs) to ChE receptors. From molecular docking analysis, noncovalent interactions especially hydrogen bonding as well as hydrophobic was found between PAPCAs and ChE. Based on the docking results, appropriate molecular structural parameters were adopted to develop a QSAR model. DFT-QSAR models for ChE enzymes demonstrated the importance of electrophilicity parameter in describing the anti-AChE and anti-BChE activities of the synthesized compounds. The correlation matrix of QSAR models and docking analysis confirmed that electrophilicity descriptor can control the influence of the hydrophobic properties of P=(O, S) and CO functional groups of PAPCA derivatives in the inhibition of human ChE enzymes. Copyright © 2014 Elsevier Inc. All rights reserved.

Incidence of malignancy in females presenting with breast lumps in OPD: a study of 277 cases

International Nuclear Information System (INIS)

Chaudhary, I.A.; Qureshi, S.K.; Rasul, S.

2003-01-01

Objective: To find the incidence of malignancy in females presenting with breast lumps in surgical out patient and to find out the age related incidence of benign and malignant diseases in these patients. Patients and Methods: All cases reporting to surgical outdoor with breast lumps were included and underwent investigation for the breast lumps to determine the histopathological diagnosis. Results: A total of 277 cases were studied. 24.2% breast lumps were malignant and 75.8% were benign. The incidence of malignancy increases from 0% in 2nd decade to 38.9% in 5th and 100% in 9th decade of life. The probability of diagnosing a breast lump as a malignant is one in three in 4th decade, two in five in 5th decade and more than one in two there after. Fibrocystic disease (33.8%) and Fibro adenoma (27.1%) was the commonest finding among the benign lumps. Among malignant lumps infiltrating duct carcinoma (68.7%) is the commonest finding. Conclusion: There is a significantly high incidence of malignant breast lumps after the 3rd decade of life and it increases subsequently. It is recommended that the surgeon managing a case of breast lump in a patient above 30 years should be highly suspicious and cautious so that early detection and management of malignant lumps be carried out. (author)

Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

International Nuclear Information System (INIS)

Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

2007-01-01

Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals

Seleção de variáveis em QSAR Variable selection in QSAR

Directory of Open Access Journals (Sweden)

Márcia Miguel Castro Ferreira

2002-05-01

Full Text Available The process of building mathematical models in quantitative structure-activity relationship (QSAR studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

Preparation of lumped fission product (FP) cross sections for a multigroup library

International Nuclear Information System (INIS)

Ono, S.; Corcuera, R.P.

1984-01-01

A method for the calculation of lumped Fission Product (FP) cross sections has been developed. The group constants fo each nuclide are generated by NJOY code, based on ENDF/B-V data. In this first version, cross section of 28 nuclides are lumped for typical characteristics of Binary Breeder Reactor (BBR). One energy group calculations are made for a 1000 MWe fast reactor to verify the influence of burnup, number of FP and fuel composition on the lumped fission product cross sections. (Author) [pt

Reduction in thermal conductivity of BiSbTe lump

Energy Technology Data Exchange (ETDEWEB)

Ahmad, Kaleem [King Saud University, Sustainable Energy Technologies Center, College of Engineering, PO Box 800, Riyadh (Saudi Arabia); Wan, C. [Tsinghua University, State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Beijing (China); Al-Eshaikh, M.A.; Kadachi, A.N. [King Saud University, Research Center, College of Engineering, PO Box 800, Riyadh (Saudi Arabia)

2017-03-15

In this work, systematic investigations on the thermal conductivities of BiSbTe lump, microstructured pristine BiSbTe bulk and single wall carbon nanotubes (SWCNTs)/BiSbTe bulk nanocomposites were performed. BiSbTe lumps were crushed to form a coarse powder (200 μm) and effect of particle size reduction on the effective thermal conductivity of BiSbTe (200 μm) bulk were analyzed. For further reduction in the conductivity, a two pronged strategy has been employed. First, additional refinement of BiSbTe (200 μm) were performed through ball milling in an inert environment. Second, SWCNTs in 0.75, and 1.0 vol% were distributed uniformly in the fine BiSbTe ball milled powder. The results showed that the effective thermal conductivities decrease with the reduction in the particle size from lump to BiSbTe (200 μm) bulk as well as with the addition of SWCNTs accompanied by further refinement of BiSbTe particles. The significant reduction in thermal conductivities of the lump was achieved for pure BiSbTe (200 μm) bulk and 0.75 vol% of SWCNTs/BiSbTe composite. This can be ascribed to the enhanced phonon scattering by the grain boundaries between the nanostructured BiSbTe particles as well as the interfaces between BiSbTe and the low dimensional carbon nanotubes. (orig.)

Neural network-based QSAR and insecticide discovery: spinetoram

Science.gov (United States)

Sparks, Thomas C.; Crouse, Gary D.; Dripps, James E.; Anzeveno, Peter; Martynow, Jacek; DeAmicis, Carl V.; Gifford, James

2008-06-01

Improvements in the efficacy and spectrum of the spinosyns, novel fermentation derived insecticide, has long been a goal within Dow AgroSciences. As large and complex fermentation products identifying specific modifications to the spinosyns likely to result in improved activity was a difficult process, since most modifications decreased the activity. A variety of approaches were investigated to identify new synthetic directions for the spinosyn chemistry including several explorations of the quantitative structure activity relationships (QSAR) of spinosyns, which initially were unsuccessful. However, application of artificial neural networks (ANN) to the spinosyn QSAR problem identified new directions for improved activity in the chemistry, which subsequent synthesis and testing confirmed. The ANN-based analogs coupled with other information on substitution effects resulting from spinosyn structure activity relationships lead to the discovery of spinetoram (XDE-175). Launched in late 2007, spinetoram provides both improved efficacy and an expanded spectrum while maintaining the exceptional environmental and toxicological profile already established for the spinosyn chemistry.

Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

Science.gov (United States)

Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

2012-08-01

The discovery of new and more potent anti-cancer agents constitutes one of the most active fields of research in chemotherapy. Colorectal cancer (CRC) is one of the most studied cancers because of its high prevalence and number of deaths. In the current pharmaceutical design of more efficient anti-CRC drugs, the use of methodologies based on Chemoinformatics has played a decisive role, including Quantitative-Structure-Activity Relationship (QSAR) techniques. However, until now, there is no methodology able to predict anti-CRC activity of compounds against more than one CRC cell line, which should constitute the principal goal. In an attempt to overcome this problem we develop here the first multi-target (mt) approach for the virtual screening and rational in silico discovery of anti-CRC agents against ten cell lines. Here, two mt-QSAR classification models were constructed using a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors while the second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted from the molecules and their contributions to anti-CRC activity were calculated using mt-QSAR-LDA model. Several fragments were identified as potential substructural features responsible for the anti-CRC activity and new molecules designed from those fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-CRC agents. Copyright © 2012 Elsevier Ltd. All rights reserved.

2D-QSAR study of fullerene nanostructure derivatives as potent HIV-1 protease inhibitors

Science.gov (United States)

Barzegar, Abolfazl; Jafari Mousavi, Somaye; Hamidi, Hossein; Sadeghi, Mehdi

2017-09-01

The protease of human immunodeficiency virus1 (HIV-PR) is an essential enzyme for antiviral treatments. Carbon nanostructures of fullerene derivatives, have nanoscale dimension with a diameter comparable to the diameter of the active site of HIV-PR which would in turn inhibit HIV. In this research, two dimensional quantitative structure-activity relationships (2D-QSAR) of fullerene derivatives against HIV-PR activity were employed as a powerful tool for elucidation the relationships between structure and experimental observations. QSAR study of 49 fullerene derivatives was performed by employing stepwise-MLR, GAPLS-MLR, and PCA-MLR models for variable (descriptor) selection and model construction. QSAR models were obtained with higher ability to predict the activity of the fullerene derivatives against HIV-PR by a correlation coefficient (R2training) of 0.942, 0.89, and 0.87 as well as R2test values of 0.791, 0.67and 0.674 for stepwise-MLR, GAPLS-MLR, and PCA -MLR models, respectively. Leave-one-out cross-validated correlation coefficient (R2CV) and Y-randomization methods confirmed the models robustness. The descriptors indicated that the HIV-PR inhibition depends on the van der Waals volumes, polarizability, bond order between two atoms and electronegativities of fullerenes derivatives. 2D-QSAR simulation without needing receptor's active site geometry, resulted in useful descriptors mainly denoting ;C60 backbone-functional groups; and ;C60 functional groups; properties. Both properties in fullerene refer to the ligand fitness and improvement van der Waals interactions with HIV-PR active site. Therefore, the QSAR models can be used in the search for novel HIV-PR inhibitors based on fullerene derivatives.

29 CFR Appendix A to Part 4022 - Lump Sum Mortality Rates

Science.gov (United States)

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Lump Sum Mortality Rates A Appendix A to Part 4022 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Pt. 4022, App. A Appendix A to Part 4022—Lump Sum Mortality...

Influences of lumped passes on welding residual stress of a thick-walled nuclear rotor steel pipe by multipass narrow gap welding

Energy Technology Data Exchange (ETDEWEB)

Tan, Long, E-mail: mse.longtan@gmail.com [State Key Laboratory for Mechanical Behavior of Materials, School of Materials Science and Engineering, Xi’an Jiaotong University, Xi’an 710049 (China); Zhang, Jianxun; Zhuang, Dong [State Key Laboratory for Mechanical Behavior of Materials, School of Materials Science and Engineering, Xi’an Jiaotong University, Xi’an 710049 (China); Liu, Chuan [Provincial Key Lab of Advanced Welding Technology, Jiangsu University of Science and Technology, Zhenjiang 212003 (China)

2014-07-01

Highlights: • The internal residual stress of the thick-walled pipe is measured by using the local removal blind hole method. • Two lumped-pass models are developed to reduce computational cost. • The effect of lumped passes on the welding residual stress is discussed. • Reasonable lumped-pass model can guarantee the accuracy and improve the computational efficiency. - Abstract: The purpose of this study is to investigate the effect of the lumped passes simulation on the distribution of residual stresses before and after heat treatment in a thick-walled nuclear power rotor pipe with a 89-pass narrow gap welding process. The local removal blind hole method was used to measure internal residual stress of the thick-walled pipe after post weld heat treatment (PWHT). Based on the ANSYS software, a two-dimensional axisymmetric finite element model is employed. Two lumped-pass models of M-5th model (five weld beads as one lumped pass) and M-10th model (ten weld beads as one lumped pass) were developed to reduce computational cost. Based on the results in this study, the distributions of residual stresses of a thick-walled welded pipe before and after PWHT are developed. Meanwhile, the distribution of the through-wall axial residual stress along the weld center line is demonstrated to be a self-equilibrating type. In addition, the investigation results show that reasonable and reliable lumped-pass model can not only guarantee the accuracy of the simulated results, but also improve the computational efficiency in the thermo-elastic–plastic FE analysis procedure. Therefore, from the viewpoint of engineering application the developed lumped-pass computational procedure is a promising and useful method to predict residual stress of large and complex welded structures.

Influences of lumped passes on welding residual stress of a thick-walled nuclear rotor steel pipe by multipass narrow gap welding

International Nuclear Information System (INIS)

Tan, Long; Zhang, Jianxun; Zhuang, Dong; Liu, Chuan

2014-01-01

Highlights: • The internal residual stress of the thick-walled pipe is measured by using the local removal blind hole method. • Two lumped-pass models are developed to reduce computational cost. • The effect of lumped passes on the welding residual stress is discussed. • Reasonable lumped-pass model can guarantee the accuracy and improve the computational efficiency. - Abstract: The purpose of this study is to investigate the effect of the lumped passes simulation on the distribution of residual stresses before and after heat treatment in a thick-walled nuclear power rotor pipe with a 89-pass narrow gap welding process. The local removal blind hole method was used to measure internal residual stress of the thick-walled pipe after post weld heat treatment (PWHT). Based on the ANSYS software, a two-dimensional axisymmetric finite element model is employed. Two lumped-pass models of M-5th model (five weld beads as one lumped pass) and M-10th model (ten weld beads as one lumped pass) were developed to reduce computational cost. Based on the results in this study, the distributions of residual stresses of a thick-walled welded pipe before and after PWHT are developed. Meanwhile, the distribution of the through-wall axial residual stress along the weld center line is demonstrated to be a self-equilibrating type. In addition, the investigation results show that reasonable and reliable lumped-pass model can not only guarantee the accuracy of the simulated results, but also improve the computational efficiency in the thermo-elastic–plastic FE analysis procedure. Therefore, from the viewpoint of engineering application the developed lumped-pass computational procedure is a promising and useful method to predict residual stress of large and complex welded structures

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

Science.gov (United States)

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

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

Science.gov (United States)

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

Science.gov (United States)

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

Fundamentals of electromagnetics 1 internal behavior of lumped elements

CERN Document Server

Voltmer, David

2007-01-01

This book is the first of two volumes which have been created to provide an understanding of the basic principles and applications of electromagnetic fields for electrical engineering students. Fundamentals of Electromagnetics Vol 1: Internal Behavior of Lumped Elements focuses upon the DC and low-frequency behavior of electromagnetic fields within lumped elements. The properties of electromagnetic fields provide the basis for predicting the terminal characteristics of resistors, capacitors, and inductors. The properties of magnetic circuits are included as well. For slightly higher frequencie

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

Science.gov (United States)

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

Science.gov (United States)

Nargotra, Amit; Sharma, Sujata; Koul, Jawahir Lal; Sangwan, Pyare Lal; Khan, Inshad Ali; Kumar, Ashwani; Taneja, Subhash Chander; Koul, Surrinder

2009-10-01

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.

A correction technique for the dispersive effects of mass lumping for transport problems

KAUST Repository

Guermond, Jean-Luc

2013-01-01

This paper addresses the well-known dispersion effect that mass lumping induces when solving transport-like equations. A simple anti-dispersion technique based on the lumped mass matrix is proposed. The method does not require any non-trivial matrix inversion and has the same anti-dispersive effects as the consistent mass matrix. A novel quasi-lumping technique for P2 finite elements is introduced. Higher-order extensions of the method are also discussed. © 2012 Elsevier B.V.

QSAR, molecular docking studies of thiophene and imidazopyridine derivatives as polo-like kinase 1 inhibitors

Science.gov (United States)

Cao, Shandong

2012-08-01

The purpose of the present study was to develop in silico models allowing for a reliable prediction of polo-like kinase inhibitors based on a large diverse dataset of 136 compounds. As an effective method, quantitative structure activity relationship (QSAR) was applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The proposed QSAR models showed reasonable predictivity of thiophene analogs (Rcv2=0.533, Rpred2=0.845) and included four molecular descriptors, namely IC3, RDF075m, Mor02m and R4e+. The optimal model for imidazopyridine derivatives (Rcv2=0.776, Rpred2=0.876) was shown to perform good in prediction accuracy, using GATS2m and BEHe1 descriptors. Analysis of the contour maps helped to identify structural requirements for the inhibitors and served as a basis for the design of the next generation of the inhibitor analogues. Docking studies were also employed to position the inhibitors into the polo-like kinase active site to determine the most probable binding mode. These studies may help to understand the factors influencing the binding affinity of chemicals and to develop alternative methods for prescreening and designing of polo-like kinase inhibitors.

QSAR Study of Skin Sensitization Using Local Lymph Node Assay Data

Directory of Open Access Journals (Sweden)

Eugene Demchuk

2004-01-01

Full Text Available Abstract: Allergic Contact Dermatitis (ACD is a common work-related skin disease that often develops as a result of repetitive skin exposures to a sensitizing chemical agent. A variety of experimental tests have been suggested to assess the skin sensitization potential. We applied a method of Quantitative Structure-Activity Relationship (QSAR to relate measured and calculated physical-chemical properties of chemical compounds to their sensitization potential. Using statistical methods, each of these properties, called molecular descriptors, was tested for its propensity to predict the sensitization potential. A few of the most informative descriptors were subsequently selected to build a model of skin sensitization. In this work sensitization data for the murine Local Lymph Node Assay (LLNA were used. In principle, LLNA provides a standardized continuous scale suitable for quantitative assessment of skin sensitization. However, at present many LLNA results are still reported on a dichotomous scale, which is consistent with the scale of guinea pig tests, which were widely used in past years. Therefore, in this study only a dichotomous version of the LLNA data was used. To the statistical end, we relied on the logistic regression approach. This approach provides a statistical tool for investigating and predicting skin sensitization that is expressed only in categorical terms of activity and nonactivity. Based on the data of compounds used in this study, our results suggest a QSAR model of ACD that is based on the following descriptors: nDB (number of double bonds, C-003 (number of CHR3 molecular subfragments, GATS6M (autocorrelation coefficient and HATS6m (GETAWAY descriptor, although the relevance of the identified descriptors to the continuous ACD QSAR has yet to be shown. The proposed QSAR model gives a percentage of positively predicted responses of 83% on the training set of compounds, and in cross validation it correctly identifies 79% of

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies.

Science.gov (United States)

Manoharan, Prabu; Vijayan, R S K; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables (X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies

Science.gov (United States)

Manoharan, Prabu; Vijayan, R. S. K.; Ghoshal, Nanda

2010-10-01

The ability to identify fragments that interact with a biological target is a key step in FBDD. To date, the concept of fragment based drug design (FBDD) is increasingly driven by bio-physical methods. To expand the boundaries of QSAR paradigm, and to rationalize FBDD using In silico approach, we propose a fragment based QSAR methodology referred here in as FB-QSAR. The FB-QSAR methodology was validated on a dataset consisting of 52 Hydroxy ethylamine (HEA) inhibitors, disclosed by GlaxoSmithKline Pharmaceuticals as potential anti-Alzheimer agents. To address the issue of target selectivity, a major confounding factor in the development of selective BACE1 inhibitors, FB-QSSR models were developed using the reported off target activity values. A heat map constructed, based on the activity and selectivity profile of the individual R-group fragments, and was in turn used to identify superior R-group fragments. Further, simultaneous optimization of multiple properties, an issue encountered in real-world drug discovery scenario, and often overlooked in QSAR approaches, was addressed using a Multi Objective (MO-QSPR) method that balances properties, based on the defined objectives. MO-QSPR was implemented using Derringer and Suich desirability algorithm to identify the optimal level of independent variables ( X) that could confer a trade-off between selectivity and activity. The results obtained from FB-QSAR were further substantiated using MIF (Molecular Interaction Fields) studies. To exemplify the potentials of FB-QSAR and MO-QSPR in a pragmatic fashion, the insights gleaned from the MO-QSPR study was reverse engineered using Inverse-QSAR in a combinatorial fashion to enumerate some prospective novel, potent and selective BACE1 inhibitors.

Efficient dynamic molecular simulation using QSAR model to know inhibition activity in breast cancer medicine

Science.gov (United States)

Zharifah, A.; Kusumowardani, E.; Saputro, A.; Sarwinda, D.

2017-07-01

According to data from GLOBOCAN (IARC) at 2012, breast cancer was the highest rated of new cancer case by 43.3 % (after controlled by age), with mortality rated as high as 12.9 %. Oncology is a major field which focusing on improving the development of drug and therapeutics cancer in pharmaceutical and biotechnology companies. Nowadays, many researchers lead to computational chemistry and bioinformatic for pharmacophore generation. A pharmacophore describes as a group of atoms in the molecule which is considered to be responsible for a pharmacological action. Prediction of biological function from chemical structure in silico modeling reduces the use of chemical reagents so the risk of environmental pollution decreased. In this research, we proposed QSAR model to analyze the composition of cancer drugs which assumed to be homogenous in character and treatment. Atomic interactions which analyzed are learned through parameters such as log p as descriptors hydrophobic, n_poinas descriptor contour strength and molecular structure, and also various concentrations inhibitor (micromolar and nanomolar) from NCBI drugs bank. The differences inhibitor activity was observed by the presence of IC 50 residues value from inhibitor substances at various concentration. Then, we got a general overview of the state of safety for drug stability seen from its IC 50 value. In our study, we also compared between micromolar and nanomolar inhibitor effect from QSAR model results. The QSAR model analysis shows that the drug concentration with nanomolar is better than micromolar, related with the content of inhibitor substances concentration. This QSAR model got the equation: Log 1/IC50 = (0.284) (±0.195) logP + (0.02) (±0.012) n_poin + (-0.005) (±0.083) Inhibition10.2nanoM + (0.1) (±0.079) Inhibition30.5nanoM + (-0.016) (±0.045) Inhibition91.5nanoM + (-2.572) (±1.570) (n = 13; r = 0.813; r2 = 0.660; s = 0.764; F = 2.720; q2 = 0.660).

The lumped parameter model for fuel pins

Energy Technology Data Exchange (ETDEWEB)

Liu, W S [Ontario Hydro, Toronto, ON (Canada)

1996-12-31

The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.

Sparse QSAR modelling methods for therapeutic and regenerative medicine

Science.gov (United States)

Winkler, David A.

2018-02-01

The quantitative structure-activity relationships method was popularized by Hansch and Fujita over 50 years ago. The usefulness of the method for drug design and development has been shown in the intervening years. As it was developed initially to elucidate which molecular properties modulated the relative potency of putative agrochemicals, and at a time when computing resources were scarce, there is much scope for applying modern mathematical methods to improve the QSAR method and to extending the general concept to the discovery and optimization of bioactive molecules and materials more broadly. I describe research over the past two decades where we have rebuilt the unit operations of the QSAR method using improved mathematical techniques, and have applied this valuable platform technology to new important areas of research and industry such as nanoscience, omics technologies, advanced materials, and regenerative medicine. This paper was presented as the 2017 ACS Herman Skolnik lecture.

Improved lumped models for transient combined convective and radiative cooling of multi-layer composite slabs

International Nuclear Information System (INIS)

An Chen; Su Jian

2011-01-01

Improved lumped parameter models were developed for the transient heat conduction in multi-layer composite slabs subjected to combined convective and radiative cooling. The improved lumped models were obtained through two-point Hermite approximations for integrals. Transient combined convective and radiative cooling of three-layer composite slabs was analyzed to illustrate the applicability of the proposed lumped models, with respect to different values of the Biot numbers, the radiation-conduction parameter, the dimensionless thermal contact resistances, the dimensionless thickness, and the dimensionless thermal conductivity. It was shown by comparison with numerical solution of the original distributed parameter model that the higher order lumped model (H 1,1 /H 0,0 approximation) yielded significant improvement of average temperature prediction over the classical lumped model. In addition, the higher order (H 1,1 /H 0,0 ) model was applied to analyze the transient heat conduction problem of steel-concrete-steel sandwich plates. - Highlights: → Improved lumped models for convective-radiative cooling of multi-layer slabs were developed. → Two-point Hermite approximations for integrals were employed. → Significant improvement over classical lumped model was achieved. → The model can be applied to high Biot number and high radiation-conduction parameter. → Transient heat conduction in steel-concrete-steel sandwich pipes was analyzed as an example.

Structural exploration for the refinement of anticancer matrix metalloproteinase-2 inhibitor designing approaches through robust validated multi-QSARs

Science.gov (United States)

Adhikari, Nilanjan; Amin, Sk. Abdul; Saha, Achintya; Jha, Tarun

2018-03-01

Matrix metalloproteinase-2 (MMP-2) is a promising pharmacological target for designing potential anticancer drugs. MMP-2 plays critical functions in apoptosis by cleaving the DNA repair enzyme namely poly (ADP-ribose) polymerase (PARP). Moreover, MMP-2 expression triggers the vascular endothelial growth factor (VEGF) having a positive influence on tumor size, invasion, and angiogenesis. Therefore, it is an urgent need to develop potential MMP-2 inhibitors without any toxicity but better pharmacokinetic property. In this article, robust validated multi-quantitative structure-activity relationship (QSAR) modeling approaches were attempted on a dataset of 222 MMP-2 inhibitors to explore the important structural and pharmacophoric requirements for higher MMP-2 inhibition. Different validated regression and classification-based QSARs, pharmacophore mapping and 3D-QSAR techniques were performed. These results were challenged and subjected to further validation to explain 24 in house MMP-2 inhibitors to judge the reliability of these models further. All these models were individually validated internally as well as externally and were supported and validated by each other. These results were further justified by molecular docking analysis. Modeling techniques adopted here not only helps to explore the necessary structural and pharmacophoric requirements but also for the overall validation and refinement techniques for designing potential MMP-2 inhibitors.

Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

Science.gov (United States)

Potemkin, Andrey V; Grishina, Maria A; Potemkin, Vladimir A

2017-01-01

In 1979, R.D.Cramer and M.Milne made a first realization of 3D comparison of molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (Dynamic Lattice- Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities. Then, in 1988, the method which was called CoMFA (Comparative Molecular Field Analysis) was introduced and the appropriate software became commercially available. Since 1988, a lot of 3D QSAR methods, algorithms and their modifications are introduced for solving of virtual drug discovery problems (e.g., CoMSIA, CoMMA, HINT, HASL, GOLPE, GRID, PARM, Raptor, BiS, CiS, ConGO,). All the methods can be divided into two groups (classes):1. Methods studying the exterior of molecules; 2) Methods studying the interior of molecules. A series of grid-based computational technologies for Continual Molecular Interior analysis (CoMIn) are invented in the current paper. The grid-based analysis is fulfilled by means of a lattice construction analogously to many other grid-based methods. The further continual elucidation of molecular structure is performed in various ways. (i) In terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum

Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

Directory of Open Access Journals (Sweden)

Hui Wang

2015-10-01

Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.

3D-QSAR and docking studies of flavonoids as potent Escherichia coli inhibitors

Science.gov (United States)

Fang, Yajing; Lu, Yulin; Zang, Xixi; Wu, Ting; Qi, XiaoJuan; Pan, Siyi; Xu, Xiaoyun

2016-01-01

Flavonoids are potential antibacterial agents. However, key substituents and mechanism for their antibacterial activity have not been fully investigated. The quantitative structure-activity relationship (QSAR) and molecular docking of flavonoids relating to potent anti-Escherichia coli agents were investigated. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed by using the pIC50 values of flavonoids. The cross-validated coefficient (q2) values for CoMFA (0.743) and for CoMSIA (0.708) were achieved, illustrating high predictive capabilities. Selected descriptors for the CoMFA model were ClogP (logarithm of the octanol/water partition coefficient), steric and electrostatic fields, while, ClogP, electrostatic and hydrogen bond donor fields were used for the CoMSIA model. Molecular docking results confirmed that half of the tested flavonoids inhibited DNA gyrase B (GyrB) by interacting with adenosine-triphosphate (ATP) pocket in a same orientation. Polymethoxyl flavones, flavonoid glycosides, isoflavonoids changed their orientation, resulting in a decrease of inhibitory activity. Moreover, docking results showed that 3-hydroxyl, 5-hydroxyl, 7-hydroxyl and 4-carbonyl groups were found to be crucial active substituents of flavonoids by interacting with key residues of GyrB, which were in agreement with the QSAR study results. These results provide valuable information for structure requirements of flavonoids as antibacterial agents. PMID:27049530

Combretastatin A-4 based thiophene derivatives as antitumor agent: Development of structure activity correlation model using 3D-QSAR, pharmacophore and docking studies

Directory of Open Access Journals (Sweden)

Vijay K. Patel

2017-12-01

Full Text Available The structure and ligand based synergistic approach is being applied to design ligands more correctly. The present report discloses the combination of structure and ligand based tactics i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling for the analysis of thiophene derivatives as anticancer agent. The main purpose of using structure and ligand based synergistic approach is to ascertain a correlation between structure and its biological activity. Thiophene derivatives have been found to possess cytotoxic activity in several cancer cell lines and its mechanism of action basically involves the binding to the colchicine site on β-tubulin. The structure based approach (molecular docking was performed on a series of thiophene derivatives. All the structures were docked to colchicine binding site of β tubulin for examining the binding affinity of compounds for antitumor activity. The pharmacophore and atom based 3D-QSAR modeling was accomplished on a series of thiophene (32 compounds analogues. Five-point common pharmacophore hypotheses (AAAAR.38 were selected for alignment of all compounds. The atom based 3D-QSAR models were developed by selection of 23 compounds as training set and 9 compounds as test set, demonstrated good partial least squares statistical results. The generated common pharmacophore hypothesis and 3D-QSAR models were validated further externally by measuring the activity of database compounds and assessing it with actual activity. The common pharmacophore hypothesis AAAAR.38 resulted in a 3D-QSAR model with excellent PLSs data for factor two characterized by the best predication coefficient Q2 (cross validated r2 (0.7213, regression R2 (0.8311, SD (0.3672, F (49.2, P (1.89E-08, RMSE (0.3864, Stability (0.8702, Pearson-r (0.8722. The results of these molecular modeling studies i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling

QSAR development and bioavailability determination: the toxicity of chloroanilines to the soil dwelling springtail Folsomia candida.

Science.gov (United States)

Giesen, Daniel; van Gestel, Cornelis A M

2013-03-01

Quantitative structure-activity relationships (QSARs) are an established tool in environmental risk assessment and a valuable alternative to the exhaustive use of test animals under REACH. In this study a QSAR was developed for the toxicity of a series of six chloroanilines to the soil-dwelling collembolan Folsomia candida in standardized natural LUFA2.2 soil. Toxicity endpoints incorporated in the QSAR were the concentrations causing 10% (EC10) and 50% (EC50) reduction in reproduction of F. candida. Toxicity was based on concentrations in interstitial water estimated from nominal concentrations in the soil and published soil-water partition coefficients. Estimated effect concentrations were negatively correlated with the lipophilicity of the compounds. Interstitial water concentrations for both the EC10 and EC50 for four compounds were determined by using solid-phase microextraction (SPME). Measured and estimated concentrations were comparable only for tetra- and pentachloroaniline. With decreasing chlorination the disparity between modelled and actual concentrations increased. Optimisation of the QSAR therefore could not be accomplished, showing the necessity to move from total soil to (bio)available concentration measurements. Copyright © 2012 Elsevier Ltd. All rights reserved.

2D-QSAR in hydroxamic acid derivatives as peptide deformylase inhibitors and antibacterial agents.

Science.gov (United States)

Gupta, Manish K; Mishra, Pradeep; Prathipati, Philip; Saxena, Anil K

2002-12-01

Peptide deformylase catalyzes the removal of N-formyl group from the N-formylmethionine of ribosome synthesized polypeptide in eubacteria. Quantitative structure-activity relationship (QSAR) studies have been carried out in a series of beta-sulfonyl and beta-sulfinyl hydroxamic acid derivatives for their PDF enzyme inhibitory and antibacterial activities against Escherichia coli DC2 and Moraxella catarrhalis RA21 which demonstrate that the PDF inhibitory activity in cell free and whole cell system increases with increase in molar refractivity and hydrophobicity. The comparison of the QSARs between the cell free and whole cell system indicate that the active binding sites in PDF isolated from E. coli and in M. catarrhalis RA21 are similar and the whole cell antibacterial activity is mainly due to the inhibition of PDF. Apart from this the QSARs on some matrixmetelloproteins (COL-1, COL-3, MAT and HME) and natural endopeptidase (NEP) indicate the possibilities of introducing selectivity in these hydroxamic acid derivatives for their PDF inhibitory activity.

HP-Lattice QSAR for dynein proteins: experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence.

Science.gov (United States)

Dea-Ayuela, María Auxiliadora; Pérez-Castillo, Yunierkis; Meneses-Marcel, Alfredo; Ubeira, Florencio M; Bolas-Fernández, Francisco; Chou, Kuo-Chen; González-Díaz, Humberto

2008-08-15

The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projects to find new molecular targets in Leishmania species including Leishmania infantum (L. infantum) and Leishmaniamajor (L. major), both important pathogens. In this sense, quantitative structure-activity relationship (QSAR) methods, which are very useful in Bioorganic and Medicinal Chemistry to discover small-sized drugs, may help to identify not only new drugs but also new drug targets, if we apply them to proteins. Dyneins are important proteins of these parasites governing fundamental processes such as cilia and flagella motion, nuclear migration, organization of the mitotic splinde, and chromosome separation during mitosis. However, despite the interest for them as potential drug targets, so far there has been no report whatsoever on dyneins with QSAR techniques. To the best of our knowledge, we report here the first QSAR for dynein proteins. We used as input the Spectral Moments of a Markov matrix associated to the HP-Lattice Network of the protein sequence. The data contain 411 protein sequences of different species selected by ClustalX to develop a QSAR that correctly discriminates on average between 92.75% and 92.51% of dyneins and other proteins in four different train and cross-validation datasets. We also report a combined experimental and theoretic study of a new dynein sequence in order to illustrate the utility of the model to search for potential drug targets with a practical example. First, we carried out a 2D-electrophoresis analysis of L. infantum biological samples. Next, we excised from 2D-E gels one spot of interest belonging to an unknown protein or protein fragment in the region Mdata base with the highest similarity score to the MS of the protein isolated from L. infantum. We used the QSAR model to predict the new sequence as dynein with probability of 99.99% without relying upon alignment. In order to confirm the previous function annotation we

Development of an ecotoxicity QSAR model for the KAshinhou Tool for Ecotoxicity (KATE) system, March 2009 version.

Science.gov (United States)

Furuhama, A; Toida, T; Nishikawa, N; Aoki, Y; Yoshioka, Y; Shiraishi, H

2010-07-01

The KAshinhou Tool for Ecotoxicity (KATE) system, including ecotoxicity quantitative structure-activity relationship (QSAR) models, was developed by the Japanese National Institute for Environmental Studies (NIES) using the database of aquatic toxicity results gathered by the Japanese Ministry of the Environment and the US EPA fathead minnow database. In this system chemicals can be entered according to their one-dimensional structures and classified by substructure. The QSAR equations for predicting the toxicity of a chemical compound assume a linear correlation between its log P value and its aquatic toxicity. KATE uses a structural domain called C-judgement, defined by the substructures of specified functional groups in the QSAR models. Internal validation by the leave-one-out method confirms that the QSAR equations, with r(2 )> 0.7, RMSE 5, give acceptable q(2) values. Such external validation indicates that a group of chemicals with an in-domain of KATE C-judgements exhibits a lower root mean square error (RMSE). These findings demonstrate that the KATE system has the potential to enable chemicals to be categorised as potential hazards.

A correction technique for the dispersive effects of mass lumping for transport problems

KAUST Repository

Guermond, Jean-Luc; Pasquetti, Richard

2013-01-01

This paper addresses the well-known dispersion effect that mass lumping induces when solving transport-like equations. A simple anti-dispersion technique based on the lumped mass matrix is proposed. The method does not require any non-trivial matrix

Cross sections of the lumped fission products for the AMZ library

International Nuclear Information System (INIS)

Ono, S.; Corcueca, R.P.; Nascimento, J.A.

1985-01-01

The preparation of the lumped fission product cross section for the AMZ library is described. For this purpose 100 nuclides were selected. The cross sections for each nuclide were generated by the NJOY code with evaluated nuclear data from ENDF/B-V, complemented with ENDF/B-IV data. A comparison is performed between the data obtained and the lumped fission product cross section of JFS-II [pt

Multiple QSAR models, pharmacophore pattern and molecular docking analysis for anticancer activity of α, β-unsaturated carbonyl-based compounds, oxime and oxime ether analogues

Science.gov (United States)

Masand, Vijay H.; El-Sayed, Nahed N. E.; Bambole, Mukesh U.; Quazi, Syed A.

2018-04-01

Multiple discrete quantitative structure-activity relationships (QSARs) models were constructed for the anticancer activity of α, β-unsaturated carbonyl-based compounds, oxime and oxime ether analogues with a variety of substituents like sbnd Br, sbnd OH, -OMe, etc. at different positions. A big pool of descriptors was considered for QSAR model building. Genetic algorithm (GA), available in QSARINS-Chem, was executed to choose optimum number and set of descriptors to create the multi-linear regression equations for a dataset of sixty-nine compounds. The newly developed five parametric models were subjected to exhaustive internal and external validation along with Y-scrambling using QSARINS-Chem, according to the OECD principles for QSAR model validation. The models were built using easily interpretable descriptors and accepted after confirming statistically robustness with high external predictive ability. The five parametric models were found to have R2 = 0.80 to 0.86, R2ex = 0.75 to 0.84, and CCCex = 0.85 to 0.90. The models indicate that frequency of nitrogen and oxygen atoms separated by five bonds from each other and internal electronic environment of the molecule have correlation with the anticancer activity.

Investigation of antigen-antibody interactions of sulfonamides with a monoclonal antibody in a fluorescence polarization immunoassay using 3D-QSAR models

Science.gov (United States)

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAbSMR) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular si...

Experimental Verification of Guided-Wave Lumped Circuits Using Waveguide Metamaterials

Science.gov (United States)

Li, Yue; Zhang, Zhijun

2018-04-01

Through the construction and characterization in microwave frequencies, we experimentally demonstrate our recently developed theory of waveguide lumped circuits, i.e., waveguide metatronics [Sci. Adv. 2, e1501790 (2016), 10.1126/sciadv.1501790], as a method to design subwavelength-scaled analog circuits. In the paradigm of waveguide metatronics, numbers of lumped inductors and capacitors are easily integrated functionally inside the waveguide, which is an irreplaceable transmission line in millimeter-wave and terahertz systems with the advantages of low radiation loss and low crosstalk. An example of multiple-ordered metatronic filters with layered structures is fabricated utilizing the technique of substrate integrated waveguides, which can be easily constructed by the printed-circuit-board process. The materials used in the construction are also typical microwave materials with positive permittivity, low loss, and negligible dispersion, imitating the plasmonic materials with negative permittivity in the optical domain. The results verify the theory of waveguide metatronics, which provides an efficient platform of functional lumped circuit design for guided-wave processing.

Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches

Directory of Open Access Journals (Sweden)

Adeena Tahir

2018-06-01

Full Text Available The bromodomain containing protein 4 (BRD4 recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r2, leave-one-out (LOO cross validated correlation coefficient (q2, bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q2 = 0.569, r2 = 0.979 and CoMSIA (q2 = 0.500, r2 = 0.982 models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94. The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds.

Simulation of hydrogen deflagration experiment – Benchmark exercise with lumped-parameter codes

Energy Technology Data Exchange (ETDEWEB)

Kljenak, Ivo, E-mail: ivo.kljenak@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Kuznetsov, Mikhail, E-mail: mike.kuznetsov@kit.edu [Karlsruhe Institute of Technology, Kaiserstraße 12, 76131 Karlsruhe (Germany); Kostka, Pal, E-mail: kostka@nubiki.hu [NUBIKI Nuclear Safety Research Institute, Konkoly-Thege Miklós út 29-33, 1121 Budapest (Hungary); Kubišova, Lubica, E-mail: lubica.kubisova@ujd.gov.sk [Nuclear Regulatory Authority of the Slovak Republic, Bajkalská 27, 82007 Bratislava (Slovakia); Maltsev, Mikhail, E-mail: maltsev_MB@aep.ru [JSC Atomenergoproekt, 1, st. Podolskykh Kursantov, Moscow (Russian Federation); Manzini, Giovanni, E-mail: giovanni.manzini@rse-web.it [Ricerca sul Sistema Energetico, Via Rubattino 54, 20134 Milano (Italy); Povilaitis, Mantas, E-mail: mantas.p@mail.lei.lt [Lithuania Energy Institute, Breslaujos g.3, 44403 Kaunas (Lithuania)

2015-03-15

Highlights: • Blind and open simulations of hydrogen combustion experiment in large-scale containment-like facility with different lumped-parameter codes. • Simulation of axial as well as radial flame propagation. • Confirmation of adequacy of lumped-parameter codes for safety analyses of actual nuclear power plants. - Abstract: An experiment on hydrogen deflagration (Upward Flame Propagation Experiment – UFPE) was proposed by the Jozef Stefan Institute (Slovenia) and performed in the HYKA A2 facility at the Karlsruhe Institute of Technology (Germany). The experimental results were used to organize a benchmark exercise for lumped-parameter codes. Six organizations (JSI, AEP, LEI, NUBIKI, RSE and UJD SR) participated in the benchmark exercise, using altogether four different computer codes: ANGAR, ASTEC, COCOSYS and ECART. Both blind and open simulations were performed. In general, all the codes provided satisfactory results of the pressure increase, whereas the results of the temperature show a wider dispersal. Concerning the flame axial and radial velocities, the results may be considered satisfactory, given the inherent simplification of the lumped-parameter description compared to the local instantaneous description.

Simulation of hydrogen deflagration experiment – Benchmark exercise with lumped-parameter codes

International Nuclear Information System (INIS)

Kljenak, Ivo; Kuznetsov, Mikhail; Kostka, Pal; Kubišova, Lubica; Maltsev, Mikhail; Manzini, Giovanni; Povilaitis, Mantas

2015-01-01

Highlights: • Blind and open simulations of hydrogen combustion experiment in large-scale containment-like facility with different lumped-parameter codes. • Simulation of axial as well as radial flame propagation. • Confirmation of adequacy of lumped-parameter codes for safety analyses of actual nuclear power plants. - Abstract: An experiment on hydrogen deflagration (Upward Flame Propagation Experiment – UFPE) was proposed by the Jozef Stefan Institute (Slovenia) and performed in the HYKA A2 facility at the Karlsruhe Institute of Technology (Germany). The experimental results were used to organize a benchmark exercise for lumped-parameter codes. Six organizations (JSI, AEP, LEI, NUBIKI, RSE and UJD SR) participated in the benchmark exercise, using altogether four different computer codes: ANGAR, ASTEC, COCOSYS and ECART. Both blind and open simulations were performed. In general, all the codes provided satisfactory results of the pressure increase, whereas the results of the temperature show a wider dispersal. Concerning the flame axial and radial velocities, the results may be considered satisfactory, given the inherent simplification of the lumped-parameter description compared to the local instantaneous description

QSAR models for reproductive toxicity and endocrine disruption in regulatory use – a preliminary investigation

DEFF Research Database (Denmark)

Jensen, Gunde Egeskov; Niemelä, Jay Russell; Wedebye, Eva Bay

2008-01-01

the new legislation. This article focuses on a screening exercise by use of our own and commercial QSAR models for identification of possible reproductive toxicants. Three QSAR models were used for reproductive toxicity for the endpoints teratogenic risk to humans (based on animal tests, clinical data...... for humans owing to possible developmental toxic effects: Xn (Harmful) and R63 (Possible risk of harm to the unborn child). The chemicals were also screened in three models for endocrine disruption....

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

Science.gov (United States)

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

BCL::EMAS — Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR

Directory of Open Access Journals (Sweden)

Mariusz Butkiewicz

2012-08-01

Full Text Available Stereochemistry is an important determinant of a molecule’s biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78. Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

Energy Technology Data Exchange (ETDEWEB)

Alves, Vinicius M. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Muratov, Eugene [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical-Chemical Institute NAS of Ukraine, Odessa 65080 (Ukraine); Fourches, Denis [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Strickland, Judy; Kleinstreuer, Nicole [ILS/Contractor Supporting the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), P.O. Box 13501, Research Triangle Park, NC 27709 (United States); Andrade, Carolina H. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States)

2015-04-15

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

International Nuclear Information System (INIS)

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

Estudos de QSAR 3D para um conjunto de inibidores de butirilcolinesterase humana QSAR 3D studies of a series of human butyrylcholinesterase inhibitors

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Humberto F. Freitas

2009-01-01

Full Text Available Alzheimer's disease (AD is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs and high predictive power (r²predict=0.88. Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.

2D-QSAR and 3D-QSAR/CoMSIA Studies on a Series of (R-2-((2-(1H-Indol-2-ylethylamino-1-Phenylethan-1-ol with Human β3-Adrenergic Activity

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Gastón Apablaza

2017-03-01

Full Text Available The β3 adrenergic receptor is raising as an important drug target for the treatment of pathologies such as diabetes, obesity, depression, and cardiac diseases among others. Several attempts to obtain selective and high affinity ligands have been made. Currently, Mirabegron is the only available drug on the market that targets this receptor approved for the treatment of overactive bladder. However, the FDA (Food and Drug Administration in USA and the MHRA (Medicines and Healthcare products Regulatory Agency in UK have made reports of potentially life-threatening side effects associated with the administration of Mirabegron, casting doubts on the continuity of this compound. Therefore, it is of utmost importance to gather information for the rational design and synthesis of new β3 adrenergic ligands. Herein, we present the first combined 2D-QSAR (two-dimensional Quantitative Structure-Activity Relationship and 3D-QSAR/CoMSIA (three-dimensional Quantitative Structure-Activity Relationship/Comparative Molecular Similarity Index Analysis study on a series of potent β3 adrenergic agonists of indole-alkylamine structure. We found a series of changes that can be made in the steric, hydrogen-bond donor and acceptor, lipophilicity and molar refractivity properties of the compounds to generate new promising molecules. Finally, based on our analysis, a summary and a regiospecific description of the requirements for improving β3 adrenergic activity is given.

Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

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Zhu, Hao; Tropsha, Alexander; Fourches, Denis; Varnek, Alexandre; Papa, Ester; Gramatica, Paola; Oberg, Tomas; Dao, Phuong; Cherkasov, Artem; Tetko, Igor V

2008-04-01

Selecting most rigorous quantitative structure-activity relationship (QSAR) approaches is of great importance in the development of robust and predictive models of chemical toxicity. To address this issue in a systematic way, we have formed an international virtual collaboratory consisting of six independent groups with shared interests in computational chemical toxicology. We have compiled an aqueous toxicity data set containing 983 unique compounds tested in the same laboratory over a decade against Tetrahymena pyriformis. A modeling set including 644 compounds was selected randomly from the original set and distributed to all groups that used their own QSAR tools for model development. The remaining 339 compounds in the original set (external set I) as well as 110 additional compounds (external set II) published recently by the same laboratory (after this computational study was already in progress) were used as two independent validation sets to assess the external predictive power of individual models. In total, our virtual collaboratory has developed 15 different types of QSAR models of aquatic toxicity for the training set. The internal prediction accuracy for the modeling set ranged from 0.76 to 0.93 as measured by the leave-one-out cross-validation correlation coefficient ( Q abs2). The prediction accuracy for the external validation sets I and II ranged from 0.71 to 0.85 (linear regression coefficient R absI2) and from 0.38 to 0.83 (linear regression coefficient R absII2), respectively. The use of an applicability domain threshold implemented in most models generally improved the external prediction accuracy but at the same time led to a decrease in chemical space coverage. Finally, several consensus models were developed by averaging the predicted aquatic toxicity for every compound using all 15 models, with or without taking into account their respective applicability domains. We find that consensus models afford higher prediction accuracy for the

The liquid lift: Looking natural without lumps

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Iñigo de Felipe

2015-01-01

Full Text Available Context: Hyaluronic acid (HA is the most common filler used to rejuvenate. Today, a three-dimensional approach prevails over previous techniques in which this material was used in specific areas of the face such as the nasolabial fold, the marionette line, and the eye trough giving a strange appearance that does not look natural. Even with a volumizing purpose, the injection of HA can sometimes produce clinically detectable nodules or lumps where the filler is deposited. Aims: To develop a new technique of injecting HA that can provide more natural results and avoid the lumpiness and nodular appearance that sometimes occurs with the injection of HA. To detect whether mixing HA with diluted anesthetic agent modifies its behavior. Settings and Design: Prospective, case control, single-center study on a private clinic setting. Materials and Methods: Eighty six patients were enrolled in this study. All of them had a previous treatment with nondiluted HA using a needle at least a year before. Patients were injected with 8 mL of reticulated HA (RHA mixed with 6 mL of saline and 2 mL of anesthetic agent. The mixture was administered through a cannula inserted in the face, one at mid-cheek and another at frontal-temporal point of entry. Owing to the lifting effect of this mixture we called this procedure liquid lift (LL. Patients were evaluated 1 month, 6 months, and a year later and asked to compare the LL with previous experiences in terms of natural look, pain, and appearance of nodules. Statistical Analysis Used: Student′s t-test. Results: One month after the treatment, 83 out of 86 patients (96.5% thought LL produced a more natural look than the previous treatment with the needle. Sixty two (72% considered LL less painful than the previous treatment and only eight (9.3% could detect lumps or nodules 1 month after LL was performed compared with 46 (53.5% that described this problem with previous needle injections. The incidence of bruising was

24 CFR 570.513 - Lump sum drawdown for financing of property rehabilitation activities.

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2010-04-01

... DEVELOPMENT BLOCK GRANTS Grant Administration § 570.513 Lump sum drawdown for financing of property... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Lump sum drawdown for financing of property rehabilitation activities. 570.513 Section 570.513 Housing and Urban Development Regulations...

QSAR studies of multidentate nitrogen ligands used in lanthanide and actinide extraction processes

International Nuclear Information System (INIS)

Drew, Michael G.B.; Hudson, Michael J.; Youngs, Tristan G.A.

2004-01-01

Quantitative structure activity relationships (QSARs) have been developed to optimise the choice of nitrogen heterocyclic molecules that can be used to separate the minor actinides such as americium(III) from europium(III) in the aqueous PUREX raffinate of nuclear waste. Experimental data on distribution coefficients and separation factors (SFs) for 47 such ligands have been obtained and show SF values ranging from 0.61 to 100. The ligands were divided into a training set of 36 molecules to develop the QSAR and a test set of 11 molecules to validate the QSAR. Over 1500 molecular descriptors were calculated for each heterocycle and the Genetic Algorithm was used to select the most appropriate for use in multiple regression equations. Equations were developed fitting the separation factors to 6-8 molecular descriptors which gave r 2 values of >0.8 for the training set and values of >0.7 for the test set, thus showing good predictive quality. The descriptors used in the equations were primarily electronic and steric. These equations can be used to predict the separation factors of nitrogen heterocycles not yet synthesised and/or tested and hence obtain the most efficient ligands for lanthanide and actinide separation

A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method

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Aiqian Zhang

2012-05-01

Full Text Available A large number of descriptors were employed to characterize the molecular structure of 53 natural, synthetic, and environmental chemicals which are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones and may thus pose a serious threat to the health of humans and wildlife. In this work, a robust quantitative structure-activity relationship (QSAR model with a novel variable selection method has been proposed for the effective estrogens. The variable selection method is based on variable interaction (VSMVI with leave-multiple-out cross validation (LMOCV to select the best subset. During variable selection, model construction and assessment, the Organization for Economic Co-operation and Development (OECD principles for regulation of QSAR acceptability were fully considered, such as using an unambiguous multiple-linear regression (MLR algorithm to build the model, using several validation methods to assessment the performance of the model, giving the define of applicability domain and analyzing the outliers with the results of molecular docking. The performance of the QSAR model indicates that the VSMVI is an effective, feasible and practical tool for rapid screening of the best subset from large molecular descriptors.

Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes.

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Toropov, Andrey A; Toropova, Alla P

2015-04-01

Available on the Internet, the CORAL software (http://www.insilico.eu/coral) has been used to build up quasi-quantitative structure-activity relationships (quasi-QSAR) for prediction of mutagenic potential of multi-walled carbon-nanotubes (MWCNTs). In contrast with the previous models built up by CORAL which were based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) the quasi-QSARs based on the representation of conditions (not on the molecular structure) such as concentration, presence (absence) S9 mix, the using (or without the using) of preincubation were encoded by so-called quasi-SMILES. The statistical characteristics of these models (quasi-QSARs) for three random splits into the visible training set and test set and invisible validation set are the following: (i) split 1: n=13, r(2)=0.8037, q(2)=0.7260, s=0.033, F=45 (training set); n=5, r(2)=0.9102, s=0.071 (test set); n=6, r(2)=0.7627, s=0.044 (validation set); (ii) split 2: n=13, r(2)=0.6446, q(2)=0.4733, s=0.045, F=20 (training set); n=5, r(2)=0.6785, s=0.054 (test set); n=6, r(2)=0.9593, s=0.032 (validation set); and (iii) n=14, r(2)=0.8087, q(2)=0.6975, s=0.026, F=51 (training set); n=5, r(2)=0.9453, s=0.074 (test set); n=5, r(2)=0.8951, s=0.052 (validation set). Copyright © 2014 Elsevier Ltd. All rights reserved.

Structural refinement and prediction of potential CCR2 antagonists through validated multi-QSAR modeling studies.

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Amin, Sk Abdul; Adhikari, Nilanjan; Baidya, Sandip Kumar; Gayen, Shovanlal; Jha, Tarun

2018-01-03

Chemokines trigger numerous inflammatory responses and modulate the immune system. The interaction between monocyte chemoattractant protein-1 and chemokine receptor 2 (CCR2) may be the cause of atherosclerosis, obesity, and insulin resistance. However, CCR2 is also implicated in other inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, asthma, and neuropathic pain. Therefore, there is a paramount importance of designing potent and selective CCR2 antagonists despite a number of drug candidates failed in clinical trials. In this article, 83 CCR2 antagonists by Jhonson and Jhonson Pharmaceuticals have been considered for robust validated multi-QSAR modeling studies to get an idea about the structural and pharmacophoric requirements for designing more potent CCR2 antagonists. All these QSAR models were validated and statistically reliable. Observations resulted from different modeling studies correlated and validated results of other ones. Finally, depending on these QSAR observations, some new molecules were proposed that may exhibit higher activity against CCR2.

A distributed lumped active all-pass network configuration.

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Huelsman, L. P.; Raghunath, S.

1972-01-01

In this correspondence a new and interesting distributed lumped active network configuration that realizes an all-pass network function is described. A design chart for determining the values of the network elements is included.

Lumped-parameters equivalent circuit for condenser microphones modeling.

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Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

2017-10-01

This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.

synthesis, screening and qsar studies of 3-benzoyl-2-oxo/thioxo

African Journals Online (AJOL)

a

divided into training and test sets. ... attention owing to their diverse range of biological properties such as calcium channel modulator [1] ... QSAR studies of antimicrobial activity represent an emerging and exceptionally important topic in the ...

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

Energy Technology Data Exchange (ETDEWEB)

Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

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Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Lumped parametric model of the human ear for sound transmission.

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Feng, Bin; Gan, Rong Z

2004-09-01

A lumped parametric model of the human auditoria peripherals consisting of six masses suspended with six springs and ten dashpots was proposed. This model will provide the quantitative basis for the construction of a physical model of the human middle ear. The lumped model parameters were first identified using published anatomical data, and then determined through a parameter optimization process. The transfer function of the middle ear obtained from human temporal bone experiments with laser Doppler interferometers was used for creating the target function during the optimization process. It was found that, among 14 spring and dashpot parameters, there were five parameters which had pronounced effects on the dynamic behaviors of the model. The detailed discussion on the sensitivity of those parameters was provided with appropriate applications for sound transmission in the ear. We expect that the methods for characterizing the lumped model of the human ear and the model parameters will be useful for theoretical modeling of the ear function and construction of the ear physical model.

QSAR models for the removal of organic micropollutants in four different river water matrices

KAUST Repository

Sudhakaran, Sairam

2012-04-01

Ozonation is an advanced water treatment process used to remove organic micropollutants (OMPs) such as pharmaceuticals and personal care products (PPCPs). In this study, Quantitative Structure Activity Relationship (QSAR) models, for ozonation and advanced oxidation process (AOP), were developed with percent-removal of OMPs by ozonation as the criterion variable. The models focused on PPCPs and pesticides elimination in bench-scale studies done within natural water matrices: Colorado River, Passaic River, Ohio River and Suwannee synthetic water. The OMPs removal for the different water matrices varied depending on the water quality conditions such as pH, DOC, alkalinity. The molecular descriptors used to define the OMPs physico-chemical properties range from one-dimensional (atom counts) to three-dimensional (quantum-chemical). Based on a statistical modeling approach using more than 40 molecular descriptors as predictors, descriptors influencing ozonation/AOP were chosen for inclusion in the QSAR models. The modeling approach was based on multiple linear regression (MLR). Also, a global model based on neural networks was created, compiling OMPs from all the four river water matrices. The chemically relevant molecular descriptors involved in the QSAR models were: energy difference between lowest unoccupied and highest occupied molecular orbital (E LUMO-E HOMO), electron-affinity (EA), number of halogen atoms (#X), number of ring atoms (#ring atoms), weakly polar component of the solvent accessible surface area (WPSA) and oxygen to carbon ratio (O/C). All the QSAR models resulted in a goodness-of-fit, R 2, greater than 0.8. Internal and external validations were performed on the models. © 2011 Elsevier Ltd.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

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Huiding Xie

2015-05-01

Full Text Available B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs, 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD. The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q2 = 0.621, r2pred = 0.885. This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors.

Science.gov (United States)

Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-05-29

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q(2) = 0.621, r(2)(pred) = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

The frequency of malignancy in breast lumps on fnac in females under 35 years of age

International Nuclear Information System (INIS)

Iqbal, M.; Iqbal, M.

2014-01-01

Breast carcinoma is one of the common malignancies in females and its incidence is increasing in younger age. Diagnosis of carcinoma breast includes clinical evaluation, imaging and pathology. Fine Needle Aspiration Cytology is the first line pathological investigation in the diagnosis with excellent results. Objective: To determine the frequency of malignancy in breast lumps on FNAC in females under 35 years of age. Descriptive cross sectional study. Setting:Department of pathology Fatima Jinnah Medical College (FJMC), Lahore. Duration: Six months from 20th July, 2011 till 20th January, 2012.Methods: 150 female patients 35 years of age or less, presenting to the OPD and Indoor of Sir Ganga Ram Hospital Lahore, an affiliated hospital of FJMC Lahore, with breast lumps were included in the study. Demographic features and consent of the patients were noted. FNAC of the patients was performed as per advice of the consultant. Diagnosis of malignant cases was further confirmed on histology.Results: Out of all, 124 lumps (82.7%) were benign and 26 lumps (17.3%) were malignant. Amongst the benign lumps, 77(62.1%) were fibroadenomas, 28(22.6%) were fibrocystic changes, 08(06.5%) were inflammatory lesions, 07(05.6%) showed pyogenic abscess and 04 lumps (03.2%) were galactoceles. Amongst the malignant lumps, 22(84.6%) were ductal carcinoma, 02(07.7%) colloid carcinoma and 02(07.7%) were malignant phylloides. Conclusions: The frequency of malignancy in breast lumps in Pakistan is significantly high in females under 35 years of age. Appropriate measures are needed for prevention and early diagnosis and treatment in young females. (author)

CLINICO PATHOLOGICAL STUDY OF BENIGN BREAST LUMP – A HOSPITAL BASED STUDY

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Anindita

2016-03-01

Full Text Available BACKGROUND Despite the fact that in majority of cases the initial symptom of benign breast disease is a lump, which can be easily detected by the patient herself by self-examination they generally present at a very late stage and this poses a great difficulty in their management. Early and appropriate diagnosis of breast disease is of utmost importance. AIM The aim of the study was to find out the relative frequency and commonest site of occurrence of benign breast disorder and their relationship with age, parity, menstrual cycle, and socio-economic status and also to find out the accuracy of investigative procedures in their diagnosis. DESIGN This is a cross sectional, interventional. Hospital based study. MATERIALS AND METHOD This study was done in 58 female patients in the age group 10 yrs. to 55 yrs. presenting with clinically benign breast lumps randomly chosen from outpatient department and indoor wards of The Calcutta Medical Research Institute, Kolkata. After taking an accurate history and proper clinical examination these patients were sequentially studied by radiological methods (Ultrasonography and mammography, fine needle aspiration cytology (FNAC and histopathology of removed specimen. Patients were enquired about their age, chief complaints, menstrual history, and use of oral pill, marital status, parity, lactation and socioeconomic status. RESULTS 79% of the benign breast lumps were found to be between 10–35 years, Fibro adenoma being the commonest one (41.38% and fibrocystic disease the second most common (29.31%. Breast lump were more common among unmarried and nulliparous females (48.27%, commonest site being upper and outer quadrant (38.8%. 69% patients were associated with an abnormal menstrual status. 76% of the cases were accurately diagnosed by clinical examination, 70% by mammography, 88% by FNAC and 84% by ultrasonography. CONCLUSION This clinicopathological study of benign breast lump is a small endeavour on our part

Lumped parameter models for the interpretation of environmental tracer data

Energy Technology Data Exchange (ETDEWEB)

Maloszewski, P [GSF-Inst. for Hydrology, Oberschleissheim (Germany); Zuber, A [Institute of Nuclear Physics, Cracow (Poland)

1996-10-01

Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs.

Lumped parameter models for the interpretation of environmental tracer data

International Nuclear Information System (INIS)

Maloszewski, P.; Zuber, A.

1996-01-01

Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs

Experimental and QSAR study on the surface activities of alkyl imidazoline surfactants

Science.gov (United States)

Kong, Xiangjun; Qian, Chengduo; Fan, Weiyu; Liang, Zupei

2018-03-01

15 alkyl imidazoline surfactants with different structures were synthesized and their critical micelle concentration (CMC) and surface tension under the CMC (σcmc) in aqueous solution were measured at 298 K. 54 kinds of molecular structure descriptors were selected as independent variables and the quantitative structure-activity relationship (QSAR) between surface activities of alkyl imidazoline and molecular structure were built through the genetic function approximation (GFA) method. Experimental results showed that the maximum surface excess of alkyl imidazoline molecules at the gas-liquid interface increased and the area occupied by each surfactant molecule and the free energies of micellization ΔGm decreased with increasing carbon number (NC) of the hydrophobic chain or decreasing hydrophilicity of counterions, which resulted in a CMC and σcmc decrease, while the log CMC and NC had a linear relationship and a negative correlation. The GFA-QSAR model, which was generated by a training set composed of 13 kinds of alkyl imidazoline though GFA method regression analysis, was highly correlated with predicted values and experimental values of the CMC. The correlation coefficient R was 0.9991, which means high prediction accuracy. The prediction error of 2 kinds of alkyl imidazoline CMCs in the Validation Set that quantitatively analyzed the influence of the alkyl imidazoline molecular structure on the CMC was less than 4%.

2D-QSAR and 3D-QSAR/CoMSIA Studies on a Series of (R)-2-((2-(1H-Indol-2-yl)ethyl)amino)-1-Phenylethan-1-ol with Human β₃-Adrenergic Activity.

Science.gov (United States)

Apablaza, Gastón; Montoya, Luisa; Morales-Verdejo, Cesar; Mellado, Marco; Cuellar, Mauricio; Lagos, Carlos F; Soto-Delgado, Jorge; Chung, Hery; Pessoa-Mahana, Carlos David; Mella, Jaime

2017-03-05

The β₃ adrenergic receptor is raising as an important drug target for the treatment of pathologies such as diabetes, obesity, depression, and cardiac diseases among others. Several attempts to obtain selective and high affinity ligands have been made. Currently, Mirabegron is the only available drug on the market that targets this receptor approved for the treatment of overactive bladder. However, the FDA (Food and Drug Administration) in USA and the MHRA (Medicines and Healthcare products Regulatory Agency) in UK have made reports of potentially life-threatening side effects associated with the administration of Mirabegron, casting doubts on the continuity of this compound. Therefore, it is of utmost importance to gather information for the rational design and synthesis of new β₃ adrenergic ligands. Herein, we present the first combined 2D-QSAR (two-dimensional Quantitative Structure-Activity Relationship) and 3D-QSAR/CoMSIA (three-dimensional Quantitative Structure-Activity Relationship/Comparative Molecular Similarity Index Analysis) study on a series of potent β₃ adrenergic agonists of indole-alkylamine structure. We found a series of changes that can be made in the steric, hydrogen-bond donor and acceptor, lipophilicity and molar refractivity properties of the compounds to generate new promising molecules. Finally, based on our analysis, a summary and a regiospecific description of the requirements for improving β₃ adrenergic activity is given.

Systematic reduction of complex tropospheric chemical mechanisms, Part II: Lumping using a time-scale based approach

Directory of Open Access Journals (Sweden)

L. E. Whitehouse

2004-01-01

Full Text Available This paper presents a formal method of species lumping that can be applied automatically to intermediate compounds within detailed and complex tropospheric chemical reaction schemes. The method is based on grouping species with reference to their chemical lifetimes and reactivity structures. A method for determining the forward and reverse transformations between individual and lumped compounds is developed. Preliminary application to the Leeds Master Chemical Mechanism (MCMv2.0 has led to the removal of 734 species and 1777 reactions from the scheme, with minimal degradation of accuracy across a wide range of test trajectories relevant to polluted tropospheric conditions. The lumped groups are seen to relate to groups of peroxy acyl nitrates, nitrates, carbonates, oxepins, substituted phenols, oxeacids and peracids with similar lifetimes and reaction rates with OH. In combination with other reduction techniques, such as sensitivity analysis and the application of the quasi-steady state approximation (QSSA, a reduced mechanism has been developed that contains 35% of the number of species and 40% of the number of reactions compared to the full mechanism. This has led to a speed up of a factor of 8 in terms of computer calculation time within box model simulations.

Using a lumped conceptual hydrological model for five different catchments in Sweden

OpenAIRE

Ekenberg, Madeleine

2016-01-01

Hydrological models offer powerful tools for understanding and predicting. In this thesis we havereviewed the advantages and disadvantages of physically based distributed hydrological models andconceptually lumped hydrological models. Based on that review, we went into depth and developed aMATLAB code to test if a simple conceptual lumped hydrological model, namely GR2M, wouldperform satisfactory for five different catchments in different parts of Sweden. The model had ratherunsatisfactory re...

Identification of phototransformation products of thalidomide and mixture toxicity assessment: an experimental and quantitative structural activity relationships (QSAR) approach.

Science.gov (United States)

Mahmoud, Waleed M M; Toolaram, Anju P; Menz, Jakob; Leder, Christoph; Schneider, Mandy; Kümmerer, Klaus

2014-02-01

The fate of thalidomide (TD) was investigated after irradiation with a medium-pressure Hg-lamp. The primary elimination of TD was monitored and structures of phototransformation products (PTPs) were assessed by LC-UV-FL-MS/MS. Environmentally relevant properties of TD and its PTPs as well as hydrolysis products (HTPs) were predicted using in silico QSAR models. Mutagenicity of TD and its PTPs was investigated in the Ames microplate format (MPF) aqua assay (Xenometrix, AG). Furthermore, a modified luminescent bacteria test (kinetic luminescent bacteria test (kinetic LBT)), using the luminescent bacteria species Vibrio fischeri, was applied for the initial screening of environmental toxicity. Additionally, toxicity of phthalimide, one of the identified PTPs, was investigated separately in the kinetic LBT. The UV irradiation eliminated TD itself without complete mineralization and led to the formation of several PTPs. TD and its PTPs did not exhibit mutagenic response in the Salmonella typhimurium strains TA 98, and TA 100 with and without metabolic activation. In contrast, QSAR analysis of PTPs and HTPs provided evidence for mutagenicity, genotoxicity and carcinogenicity using additional endpoints in silico software. QSAR analysis of different ecotoxicological endpoints, such as acute toxicity towards V. fischeri, provided positive alerts for several identified PTPs and HTPs. This was partially confirmed by the results of the kinetic LBT, in which a steady increase of acute and chronic toxicity during the UV-treatment procedure was observed for the photolytic mixtures at the highest tested concentration. Moreover, the number of PTPs within the reaction mixture that might be responsible for the toxification of TD during UV-treatment was successfully narrowed down by correlating the formation kinetics of PTPs with QSAR predictions and experimental toxicity data. Beyond that, further analysis of the commercially available PTP phthalimide indicated that transformation of

Comparative analysis of pharmaceuticals versus industrial chemicals acute aquatic toxicity classification according to the United Nations classification system for chemicals. Assessment of the (Q)SAR predictability of pharmaceuticals acute aquatic toxicity and their predominant acute toxic mode-of-action

DEFF Research Database (Denmark)

Sanderson, Hans; Thomsen, Marianne

2009-01-01

data. Pharmaceuticals were found to be more frequent than industrial chemicals in GHS category III. Acute toxicity was predictable (>92%) using a generic (Q)SAR ((Quantitative) Structure Activity Relationship) suggesting a narcotic MOA. Analysis of model prediction error suggests that 68...

APPROACH TO THE DIAGNOSIS OF A BREAST LUMP

African Journals Online (AJOL)

breast cancer in any woman, irrespective of age.1,2 Fortunately, the vast majority of breast lumps are ... malignant breast lesions can be diagnosed in this way. When all aspects ... ultrasonography is the preferred modality for women under 35 ...

Development of a transient, lumped hydrologic model for geomorphologic units in a geomorphology based rainfall-runoff modelling framework

Science.gov (United States)

Vannametee, E.; Karssenberg, D.; Hendriks, M. R.; de Jong, S. M.; Bierkens, M. F. P.

2010-05-01

We propose a modelling framework for distributed hydrological modelling of 103-105 km2 catchments by discretizing the catchment in geomorphologic units. Each of these units is modelled using a lumped model representative for the processes in the unit. Here, we focus on the development and parameterization of this lumped model as a component of our framework. The development of the lumped model requires rainfall-runoff data for an extensive set of geomorphological units. Because such large observational data sets do not exist, we create artificial data. With a high-resolution, physically-based, rainfall-runoff model, we create artificial rainfall events and resulting hydrographs for an extensive set of different geomorphological units. This data set is used to identify the lumped model of geomorphologic units. The advantage of this approach is that it results in a lumped model with a physical basis, with representative parameters that can be derived from point-scale measurable physical parameters. The approach starts with the development of the high-resolution rainfall-runoff model that generates an artificial discharge dataset from rainfall inputs as a surrogate of a real-world dataset. The model is run for approximately 105 scenarios that describe different characteristics of rainfall, properties of the geomorphologic units (i.e. slope gradient, unit length and regolith properties), antecedent moisture conditions and flow patterns. For each scenario-run, the results of the high-resolution model (i.e. runoff and state variables) at selected simulation time steps are stored in a database. The second step is to develop the lumped model of a geomorphological unit. This forward model consists of a set of simple equations that calculate Hortonian runoff and state variables of the geomorphologic unit over time. The lumped model contains only three parameters: a ponding factor, a linear reservoir parameter, and a lag time. The model is capable of giving an appropriate

Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

Science.gov (United States)

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-04-01

Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q 2 of 0.578, R 2 of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 of 0.554, R 2 of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r 2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

Science.gov (United States)

Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

2016-03-15

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

Modelling of nonhomogeneous atmosphere in NPP containment using lumped-parameter model based on CFD calculations

International Nuclear Information System (INIS)

Ivo, Kljenak; Miroslav, Babic; Borut, Mavko

2007-01-01

The possibility of simulating adequately the flow circulation within a nuclear power plant containment using a lumped-parameter code is considered. An experiment on atmosphere mixing and stratification, which was performed in the containment experimental facility TOSQAN at IRSN (Institute of Radioprotection and Nuclear Safety) in Saclay (France), was simulated with the CFD (Computational Fluid Dynamics) code CFX4 and the lumped-parameter code CONTAIN. During some phases of the experiment, steady states were achieved by keeping the boundary conditions constant. Two steady states during which natural convection was the dominant gas flow mechanism were simulated independently. The nodalization of the lumped-parameter model was based on the flow pattern, simulated with the CFD code. The simulation with the lumped-parameter code predicted basically the same flow circulation patterns within the experimental vessel as the simulation with the CFD code did. (authors)

Mixed lump-kink and rogue wave-kink solutions for a (3 + 1) -dimensional B-type Kadomtsev-Petviashvili equation in fluid mechanics

Science.gov (United States)

Hu, Cong-Cong; Tian, Bo; Wu, Xiao-Yu; Yuan, Yu-Qiang; Du, Zhong

2018-02-01

Under investigation is a (3 + 1) -dimensional B-type Kadomtsev-Petviashvili equation, which describes the weakly dispersive waves in a fluid. Via the Hirota method and symbolic computation, we obtain the mixed lump-kink and mixed rogue wave-kink solutions. Through the mixed lump-kink solutions, we observe three different phenomena between a lump and one kink. For the fusion phenomenon, a lump and a kink are merged with the lump's energy transferring into the kink gradually, until the lump merges into the kink completely. Fission phenomenon displays that a lump separates from a kink. The last phenomenon shows that a lump travels together with a kink with their amplitudes unchanged. In addition, we graphically study the interaction between a rogue wave and a pair of the kinks. It can be observed that the rogue wave arises from one kink and disappears into the other kink. At certain time, the amplitude of the rogue wave reaches the maximum.

Optimal Component Lumping: problem formulation and solution techniques

DEFF Research Database (Denmark)

Lin, Bao; Leibovici, Claude F.; Jørgensen, Sten Bay

2008-01-01

This paper presents a systematic method for optimal lumping of a large number of components in order to minimize the loss of information. In principle, a rigorous composition-based model is preferable to describe a system accurately. However, computational intensity and numerical issues restrict ...

Fission and fusion interaction phenomena of mixed lump kink solutions for a generalized (3+1)-dimensional B-type Kadomtsev-Petviashvili equation

Science.gov (United States)

Liu, Yaqing; Wen, Xiaoyong

2018-05-01

In this paper, a generalized (3+1)-dimensional B-type Kadomtsev-Petviashvili (gBKP) equation is investigated by using the Hirota’s bilinear method. With the aid of symbolic computation, some new lump, mixed lump kink and periodic lump solutions are derived. Based on the derived solutions, some novel interaction phenomena like the fission and fusion interactions between one lump soliton and one kink soliton, the fission and fusion interactions between one lump soliton and a pair of kink solitons and the interactions between two periodic lump solitons are discussed graphically. Results might be helpful for understanding the propagation of the shallow water wave.

Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

Directory of Open Access Journals (Sweden)

Marius Lazea

2011-12-01

Full Text Available The classical method of quantitative structure-activity relationships (QSAR is enriched using non-linear models, as Thom’s polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the “optimal molecular structural domains” and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.

Novel 1,4-naphthoquinone-based sulfonamides: Synthesis, QSAR, anticancer and antimalarial studies.

Science.gov (United States)

Pingaew, Ratchanok; Prachayasittikul, Veda; Worachartcheewan, Apilak; Nantasenamat, Chanin; Prachayasittikul, Supaluk; Ruchirawat, Somsak; Prachayasittikul, Virapong

2015-10-20

A novel series of 1,4-naphthoquinones (33-44) tethered by open and closed chain sulfonamide moieties were designed, synthesized and evaluated for their cytotoxic and antimalarial activities. All quinone-sulfonamide derivatives displayed a broad spectrum of cytotoxic activities against all of the tested cancer cell lines including HuCCA-1, HepG2, A549 and MOLT-3. Most quinones (33-36 and 38-43) exerted higher anticancer activity against HepG2 cell than that of the etoposide. The open chain analogs 36 and 42 were shown to be the most potent compounds. Notably, the restricted sulfonamide analog 38 with 6,7-dimethoxy groups exhibited the most potent antimalarial activity (IC₅₀ = 2.8 μM). Quantitative structure-activity relationships (QSAR) study was performed to reveal important chemical features governing the biological activities. Five constructed QSAR models provided acceptable predictive performance (Rcv 0.5647-0.9317 and RMSEcv 0.1231-0.2825). Four additional sets of structurally modified compounds were generated in silico (34a-34d, 36a-36k, 40a-40d and 42a-42k) in which their activities were predicted using the constructed QSAR models. A comprehensive discussion of the structure-activity relationships was made and a set of promising compounds (i.e., 33, 36, 38, 42, 36d, 36f, 42e, 42g and 42f) was suggested for further development as anticancer and antimalarial agents. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems

Science.gov (United States)

Meng, Luming; Sheong, Fu Kit; Zeng, Xiangze; Zhu, Lizhe; Huang, Xuhui

2017-07-01

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist. Here, we have developed a path lumping method to group these parallel pathways into metastable path channels for analysis. We define the similarity between two pathways as the intercrossing flux between them and then apply the spectral clustering algorithm to lump these pathways into groups. We demonstrate the power of our method by applying it to two systems: a 2D-potential consisting of four metastable energy channels and the hydrophobic collapse process of two hydrophobic molecules. In both cases, our algorithm successfully reveals the metastable path channels. We expect this path lumping algorithm to be a promising tool for revealing unprecedented insights into the kinetic mechanisms of complex multi-body processes.

Does rational selection of training and test sets improve the outcome of QSAR modeling?

Science.gov (United States)

Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

2012-10-22

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

Intermittent reservoir daily-inflow prediction using lumped and ...

Indian Academy of Sciences (India)

For the present case study considered, both MLR and ARIMA models performed ... is to be remembered that the transformation of ... Multi-linear regression; lumped and distributed data; time-series models; cause-effect ... flow data are short for adequate system study. ..... that the standard deviation, skewness, kurtosis.

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

Energy Technology Data Exchange (ETDEWEB)

Alves, Vinicius M. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Muratov, Eugene [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical–Chemical Institute NAS of Ukraine, Odessa 65080 (Ukraine); Fourches, Denis [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Strickland, Judy; Kleinstreuer, Nicole [ILS/Contractor supporting the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), P.O. Box 13501, Research Triangle Park, NC 27709 (United States); Andrade, Carolina H. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States)

2015-04-15

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R{sup 2} = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q{sup 2}{sub ext} = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

International Nuclear Information System (INIS)

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R 2 = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q 2 ext = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin sensitization and

A combined QSAR and partial order ranking approach to risk assessment.

Science.gov (United States)

Carlsen, L

2006-04-01

QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.

Common SAR Derived from Linear and Non-linear QSAR Studies on AChE Inhibitors used in the Treatment of Alzheimer's Disease.

Science.gov (United States)

Pulikkal, Babitha Pallikkara; Marunnan, Sahila Mohammed; Bandaru, Srinivas; Yadav, Mukesh; Nayarisseri, Anuraj; Sureshkumar, Sivanpillai

2017-11-14

Deficits in cholinergic neurotransmission due to the degeneration of cholinergic neurons in the brain are believed to be one of the major causes of the memory impairments associated with AD. Targeting acetyl cholinesterase (AChE) surfaced as a potential therapeutic target in the treatment of Alzheimer's disease. The present study is pursued to develop quantitative structure activity relationship (QSAR) models to determine chemical descriptors responsible for AChE activity. Two different sets of AChE inhibitors, dataset-I (30 compounds) and dataset-II (20 compounds) were investigated through MLR aided linear and SVM aided non-linear QSAR models. The obtained QSAR models were found statistically fit, stable and predictive on validation scales. These QSAR models were further investigated for their common structure-activity relationship in terms of overlapping molecular descriptors selection. Atomic mass weighted 3D Morse descriptors (MATS5m) and Radial Distribution Function (RDF045m) descriptors were found in common SAR for both the datasets. Electronegativity weighted (MATS5e, HATSe, and Mor17e) descriptors have also been identified in regulative roles towards endpoint values of dataset-I and dataset-II. The common SAR identified in these linear and non-linear QSAR models could be utilized to design novel inhibitors of AChE with improved biological activity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Lumping procedure for a kinetic model of catalytic naphtha reforming

Directory of Open Access Journals (Sweden)

H. M. Arani

2009-12-01

Full Text Available A lumping procedure is developed for obtaining kinetic and thermodynamic parameters of catalytic naphtha reforming. All kinetic and deactivation parameters are estimated from industrial data and thermodynamic parameters are calculated from derived mathematical expressions. The proposed model contains 17 lumps that include the C6 to C8+ hydrocarbon range and 15 reaction pathways. Hougen-Watson Langmuir-Hinshelwood type reaction rate expressions are used for kinetic simulation of catalytic reactions. The kinetic parameters are benchmarked with several sets of plant data and estimated by the SQP optimization method. After calculation of deactivation and kinetic parameters, plant data are compared with model predictions and only minor deviations between experimental and calculated data are generally observed.

QSAR study on the histamine (H3 receptor antagonists using the genetic algorithm: Multi parameter linear regression

Directory of Open Access Journals (Sweden)

Adimi Maryam

2012-01-01

Full Text Available A quantitative structure activity relationship (QSAR model has been produced for predicting antagonist potency of biphenyl derivatives as human histamine (H3 receptors. The molecular structures of the compounds are numerically represented by various kinds of molecular descriptors. The whole data set was divided into training and test sets. Genetic algorithm based multiple linear regression is used to select most statistically effective descriptors. The final QSAR model (N =24, R2=0.916, F = 51.771, Q2 LOO = 0.872, Q2 LGO = 0.847, Q2 BOOT = 0.857 was fully validated employing leaveone- out (LOO cross-validation approach, Fischer statistics (F, Yrandomisation test, and predictions based on the test data set. The test set presented an external prediction power of R2 test=0.855. In conclusion, the QSAR model generated can be used as a valuable tool for designing similar groups of new antagonists of histamine (H3 receptors.

QSAR screening of 70,983 REACH substances for genotoxic carcinogenicity, mutagenicity and developmental toxicity in the ChemScreen project

DEFF Research Database (Denmark)

Wedebye, Eva Bay; Dybdahl, Marianne; Nikolov, Nikolai Georgiev

2015-01-01

The ChemScreen project aimed to develop a screening system for reproductive toxicity based on alternative methods. QSARs can, if adequate, contribute to the evaluation of chemical substances under REACH and may in some cases be applied instead of experimental testing to fill data gaps...... for information requirements. As no testing for reproductive effects should be performed in REACH on known genotoxic carcinogens or germ cell mutagens with appropriate risk management measures implemented, a QSAR pre-screen for 70,983 REACH substances was performed. Sixteen models and three decision algorithms...... were used to reach overall predictions of substances with potential effects with the following result: 6.5% genotoxic carcinogens, 16.3% mutagens, 11.5% developmental toxicants. These results are similar to findings in earlier QSAR and experimental studies of chemical inventories, and illustrate how...

Role of cytological grading in the management of breast lump

International Nuclear Information System (INIS)

Mehmood, A.; Ahmed, M.; Jamal, S.

2003-01-01

Objective: To evaluate the fine needle aspiration (FNA) smears of the breast lumps using the cytological evaluation system (C1 to C5) as practiced in the National Breast Screening Programme in the UK. Results: A total of 75 patients of lump breast were included in the project. The age range was 13-75 years with a peak incidence in the 3rd decade. There were 70 (93.3%) females and 5 (6.6%) male cases. Of the total 75 cases, 7 were designated C1, 45 C2, 5 C3, 7 C4 and 11 C5. In surgical biopsies, all the 45 cases designated as C2 proved to be benign with fibroadenoma and fibrocystic change as predominant lesions. All 11 designated C5 proved to be malignant; whereas, of the 5 cases labeled as C3, 4 were benign and one was malignant and out of seven C4 cases, 5 came out as malignant and 2 proved benign. Conclusion: the fine needle aspiration of lump breast has a sensitivity of 94.1%, specificity of 96.0% and accuracy of 95.5%. The C1-C5 grading system is practical, flexible, and gives room for expression of opinion by cytopathologist and easily interpreted by clincians. (author)

Dynamics of lumps and dark-dark solitons in the multi-component long-wave-short-wave resonance interaction system

Science.gov (United States)

Rao, Jiguang; Porsezian, Kuppuswamy; He, Jingsong; Kanna, Thambithurai

2018-01-01

General semi-rational solutions of an integrable multi-component (2+1)-dimensional long-wave-short-wave resonance interaction system comprising multiple short waves and a single long wave are obtained by employing the bilinear method. These solutions describe the interactions between various types of solutions, including line rogue waves, lumps, breathers and dark solitons. We only focus on the dynamical behaviours of the interactions between lumps and dark solitons in this paper. Our detailed study reveals two different types of excitation phenomena: fusion and fission. It is shown that the fundamental (simplest) semi-rational solutions can exhibit fission of a dark soliton into a lump and a dark soliton or fusion of one lump and one dark soliton into a dark soliton. The non-fundamental semi-rational solutions are further classified into three subclasses: higher-order, multi- and mixed-type semi-rational solutions. The higher-order semi-rational solutions show the process of annihilation (production) of two or more lumps into (from) one dark soliton. The multi-semi-rational solutions describe N(N≥2) lumps annihilating into or producing from N-dark solitons. The mixed-type semi-rational solutions are a hybrid of higher-order semi-rational solutions and multi-semi-rational solutions. For the mixed-type semi-rational solutions, we demonstrate an interesting dynamical behaviour that is characterized by partial suppression or creation of lumps from the dark solitons.

Dynamics of lumps and dark-dark solitons in the multi-component long-wave-short-wave resonance interaction system.

Science.gov (United States)

Rao, Jiguang; Porsezian, Kuppuswamy; He, Jingsong; Kanna, Thambithurai

2018-01-01

General semi-rational solutions of an integrable multi-component (2+1)-dimensional long-wave-short-wave resonance interaction system comprising multiple short waves and a single long wave are obtained by employing the bilinear method. These solutions describe the interactions between various types of solutions, including line rogue waves, lumps, breathers and dark solitons. We only focus on the dynamical behaviours of the interactions between lumps and dark solitons in this paper. Our detailed study reveals two different types of excitation phenomena: fusion and fission. It is shown that the fundamental (simplest) semi-rational solutions can exhibit fission of a dark soliton into a lump and a dark soliton or fusion of one lump and one dark soliton into a dark soliton. The non-fundamental semi-rational solutions are further classified into three subclasses: higher-order, multi- and mixed-type semi-rational solutions. The higher-order semi-rational solutions show the process of annihilation (production) of two or more lumps into (from) one dark soliton. The multi-semi-rational solutions describe N ( N ≥2) lumps annihilating into or producing from N -dark solitons. The mixed-type semi-rational solutions are a hybrid of higher-order semi-rational solutions and multi-semi-rational solutions. For the mixed-type semi-rational solutions, we demonstrate an interesting dynamical behaviour that is characterized by partial suppression or creation of lumps from the dark solitons.

Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

Science.gov (United States)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional

Lumped Mass Modeling for Local-Mode-Suppressed Element Connectivity

DEFF Research Database (Denmark)

Joung, Young Soo; Yoon, Gil Ho; Kim, Yoon Young

2005-01-01

connectivity parameterization (ECP) is employed. On the way to the ultimate crashworthy structure optimization, we are now developing a local mode-free topology optimization formulation that can be implemented in the ECP method. In fact, the local mode-freeing strategy developed here can be also used directly...... experiencing large structural changes, appears to be still poor. In ECP, the nodes of the domain-discretizing elements are connected by zero-length one-dimensional elastic links having varying stiffness. For computational efficiency, every elastic link is now assumed to have two lumped masses at its ends....... Choosing appropriate penalization functions for lumped mass and link stiffness is important for local mode-free results. However, unless the objective and constraint functions are carefully selected, it is difficult to obtain clear black-and-white results. It is shown that the present formulation is also...

Parameters for Pyrethroid Insecticide QSAR and PBPK/PD Models for Human Risk Assessment

Science.gov (United States)

This pyrethroid insecticide parameter review is an extension of our interest in developing quantitative structure–activity relationship–physiologically based pharmacokinetic/pharmacodynamic (QSAR-PBPK/PD) models for assessing health risks, which interest started with the organoph...

A Lumped Thermal Model Including Thermal Coupling and Thermal Boundary Conditions for High Power IGBT Modules

DEFF Research Database (Denmark)

Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede

2018-01-01

Detailed thermal dynamics of high power IGBT modules are important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated thermal behavior in the IGBTs: The typically used...... thermal model based on one-dimensional RC lumps have limits to provide temperature distributions inside the device, moreover some variable factors in the real-field applications like the cooling and heating conditions of the converter cannot be adapted. On the other hand, the more advanced three......-dimensional thermal models based on Finite Element Method (FEM) need massive computations, which make the long-term thermal dynamics difficult to calculate. In this paper, a new lumped three-dimensional thermal model is proposed, which can be easily characterized from FEM simulations and can acquire the critical...

Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

Science.gov (United States)

Verma, Rajeshwar P; Matthews, Edwin J

2015-03-01

Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1, 4-dihydropyridine derivatives with potential antihypertensive effects.

Science.gov (United States)

Jardínez, Christiaan; Vela, Alberto; Cruz-Borbolla, Julián; Alvarez-Mendez, Rodrigo J; Alvarado-Rodríguez, José G

2016-12-01

The relationship between the chemical structure and biological activity (log IC 50 ) of 40 derivatives of 1,4-dihydropyridines (DHPs) was studied using density functional theory (DFT) and multiple linear regression analysis methods. With the aim of improving the quantitative structure-activity relationship (QSAR) model, the reduced density gradient s( r) of the optimized equilibrium geometries was used as a descriptor to include weak non-covalent interactions. The QSAR model highlights the correlation between the log IC 50 with highest molecular orbital energy (E HOMO ), molecular volume (V), partition coefficient (log P), non-covalent interactions NCI(H4-G) and the dual descriptor [Δf(r)]. The model yielded values of R 2 =79.57 and Q 2 =69.67 that were validated with the next four internal analytical validations DK=0.076, DQ=-0.006, R P =0.056, and R N =0.000, and the external validation Q 2 boot =64.26. The QSAR model found can be used to estimate biological activity with high reliability in new compounds based on a DHP series. Graphical abstract The good correlation between the log IC 50 with the NCI (H4-G) estimated by the reduced density gradient approach of the DHP derivatives.

A comparative QSAR study on the estrogenic activities of persistent organic pollutants by PLS and SVM

Directory of Open Access Journals (Sweden)

Fei Li

2015-11-01

Full Text Available Quantitative structure-activity relationships (QSARs were determined using partial least square (PLS and support vector machine (SVM. The predicted values by the final QSAR models were in good agreement with the corresponding experimental values. Chemical estrogenic activities are related to atomic properties (atomic Sanderson electronegativities, van der Waals volumes and polarizabilities. Comparison of the results obtained from two models, the SVM method exhibited better overall performances. Besides, three PLS models were constructed for some specific families based on their chemical structures. These predictive models should be useful to rapidly identify potential estrogenic endocrine disrupting chemicals.

A lumped parameter model of plasma focus

International Nuclear Information System (INIS)

Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro

1999-01-01

A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

Science.gov (United States)

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving the applicability of (Q)SARs for percutaneous penetration in regulatory risk assessment.

NARCIS (Netherlands)

Bouwman, T.; Cronin, M.T.; Bessems, J.G.; Sandt, J.J. van de

2008-01-01

The new regulatory framework REACH (Registration, Evaluation, and Authorisation of Chemicals) foresees the use of non-testing approaches, such as read-across, chemical categories, structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs). Although information

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

Science.gov (United States)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

Management of breast lumps in Maiduguri, Nigeria

Directory of Open Access Journals (Sweden)

Ali Nuhu

2014-01-01

Full Text Available Background: Reported changes in the demography, modes of presentation and histological variants of tumors of the breast have been published in developed and some developing countries. Although benign lesions have persistently accounted for most breast tumors, the incidence of malignant breast lesion in young women in sub-Saharan Africa has been disturbingly high. We reviewed the demographics, pattern and management of breast lumps excised at University of Maiduguri Teaching Hospital (UMTH over a 6 year period. Patients and Methods: A retrospective study of patients with breast lumps at UMTH was carried out between January 2005 and December 2010. Details of their bio-data, clinical, and histopathology details were analyzed using descriptive statistics. Results: A total of 913 patients, comprising 887 females (97.2% and 26 males (2.8% were reviewed. The mean age was 33.1 ± 14.6 years (range: 12-80 years and the mean duration of symptoms was 8 ± 2.14 months (range: 2-23 months. 359 (39.3% were malignant and 577 (63.2% were benign. The mean ages of women and men with invasive carcinomas of the breast were 45.58 ± 13.22 and 49.75 ± 18.28 years, respectively. The mean age of women with benign breast disease was 28.4 ± 10.0 for fibrocystic disease and 21.8 ± 5.31 years for fibroadenoma. Mode of presentations included ulcers (8.7%, axillary lymph node enlargement (30.0%, nipple discharge (13.0% and breast pain (21.7%. The most common histological diagnoses were carcinoma of the breast, N = 340 (37.2%, fibroadenoma, N = 276 (30.2% and fibrocystic disease, N = 199 (21.8%. The least common pathology was tuberculosis of the breast, N = 6; (0.7%. Conclusion: Though benign diseases are still more common, a high percentage of breast lumps in Maiduguri are due to malignant disease and this is frequent in younger women.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

Science.gov (United States)

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

29 CFR Appendix C to Part 4022 - Lump Sum Interest Rates for Private-Sector Payments

Science.gov (United States)

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Lump Sum Interest Rates for Private-Sector Payments C Appendix C to Part 4022 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY... Appendix C to Part 4022—Lump Sum Interest Rates for Private-Sector Payments [In using this table: (1) For...

Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

Science.gov (United States)

Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

2013-06-01

Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

Construction and analysis of a human hepatotoxicity database suitable for QSAR modeling using post-market safety data

International Nuclear Information System (INIS)

Zhu, Xiao; Kruhlak, Naomi L.

2014-01-01

Graphical abstract: - Abstract: Drug-induced liver injury (DILI) is one of the most common drug-induced adverse events (AEs) leading to life-threatening conditions such as acute liver failure. It has also been recognized as the single most common cause of safety-related post-market withdrawals or warnings. Efforts to develop new predictive methods to assess the likelihood of a drug being a hepatotoxicant have been challenging due to the complexity and idiosyncrasy of clinical manifestations of DILI. The FDA adverse event reporting system (AERS) contains post-market data that depict the morbidity of AEs. Here, we developed a scalable approach to construct a hepatotoxicity database using post-market data for the purpose of quantitative structure–activity relationship (QSAR) modeling. A set of 2029 unique and modelable drug entities with 13,555 drug-AE combinations was extracted from the AERS database using 37 hepatotoxicity-related query preferred terms (PTs). In order to determine the optimal classification scheme to partition positive from negative drugs, a manually-curated DILI calibration set composed of 105 negatives and 177 positives was developed based on the published literature. The final classification scheme combines hepatotoxicity-related PT data with supporting information that optimize the predictive performance across the calibration set. Data for other toxicological endpoints related to liver injury such as liver enzyme abnormalities, cholestasis, and bile duct disorders, were also extracted and classified. Collectively, these datasets can be used to generate a battery of QSAR models that assess a drug's potential to cause DILI

A 3D QSAR pharmacophore model and quantum chemical structure--activity analysis of chloroquine(CQ)-resistance reversal.

Science.gov (United States)

Bhattacharjee, Apurba K; Kyle, Dennis E; Vennerstrom, Jonathan L; Milhous, Wilbur K

2002-01-01

Using CATALYST, a three-dimensional QSAR pharmacophore model for chloroquine(CQ)-resistance reversal was developed from a training set of 17 compounds. These included imipramine (1), desipramine (2), and 15 of their analogues (3-17), some of which fully reversed CQ-resistance, while others were without effect. The generated pharmacophore model indicates that two aromatic hydrophobic interaction sites on the tricyclic ring and a hydrogen bond acceptor (lipid) site at the side chain, preferably on a nitrogen atom, are necessary for potent activity. Stereoelectronic properties calculated by using AM1 semiempirical calculations were consistent with the model, particularly the electrostatic potential profiles characterized by a localized negative potential region by the side chain nitrogen atom and a large region covering the aromatic ring. The calculated data further revealed that aminoalkyl substitution at the N5-position of the heterocycle and a secondary or tertiary aliphatic aminoalkyl nitrogen atom with a two or three carbon bridge to the heteroaromatic nitrogen (N5) are required for potent "resistance reversal activity". Lowest energy conformers for 1-17 were determined and optimized to afford stereoelectronic properties such as molecular orbital energies, electrostatic potentials, atomic charges, proton affinities, octanol-water partition coefficients (log P), and structural parameters. For 1-17, fairly good correlation exists between resistance reversal activity and intrinsic basicity of the nitrogen atom at the tricyclic ring system, frontier orbital energies, and lipophilicity. Significantly, nine out of 11 of a group of structurally diverse CQ-resistance reversal agents mapped very well on the 3D QSAR pharmacophore model.

Effect of dissolved organic matter on pre-equilibrium passive sampling: A predictive QSAR modeling study.

Science.gov (United States)

Lin, Wei; Jiang, Ruifen; Shen, Yong; Xiong, Yaxin; Hu, Sizi; Xu, Jianqiao; Ouyang, Gangfeng

2018-04-13

Pre-equilibrium passive sampling is a simple and promising technique for studying sampling kinetics, which is crucial to determine the distribution, transfer and fate of hydrophobic organic compounds (HOCs) in environmental water and organisms. Environmental water samples contain complex matrices that complicate the traditional calibration process for obtaining the accurate rate constants. This study proposed a QSAR model to predict the sampling rate constants of HOCs (polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and pesticides) in aqueous systems containing complex matrices. A homemade flow-through system was established to simulate an actual aqueous environment containing dissolved organic matter (DOM) i.e. humic acid (HA) and (2-Hydroxypropyl)-β-cyclodextrin (β-HPCD)), and to obtain the experimental rate constants. Then, a quantitative structure-activity relationship (QSAR) model using Genetic Algorithm-Multiple Linear Regression (GA-MLR) was found to correlate the experimental rate constants to the system state including physicochemical parameters of the HOCs and DOM which were calculated and selected as descriptors by Density Functional Theory (DFT) and Chem 3D. The experimental results showed that the rate constants significantly increased as the concentration of DOM increased, and the enhancement factors of 70-fold and 34-fold were observed for the HOCs in HA and β-HPCD, respectively. The established QSAR model was validated as credible (R Adj. 2 =0.862) and predictable (Q 2 =0.835) in estimating the rate constants of HOCs for complex aqueous sampling, and a probable mechanism was developed by comparison to the reported theoretical study. The present study established a QSAR model of passive sampling rate constants and calibrated the effect of DOM on the sampling kinetics. Copyright © 2018 Elsevier B.V. All rights reserved.

Rogue waves and lump solutions for a (3+1)-dimensional generalized B-type Kadomtsev-Petviashvili equation in fluid mechanics

Science.gov (United States)

Wu, Xiao-Yu; Tian, Bo; Chai, Han-Peng; Sun, Yan

2017-08-01

Under investigation in this letter is a (3+1)-dimensional generalized B-type Kadomtsev-Petviashvili equation, which describes the weakly dispersive waves propagating in a fluid. Employing the Hirota method and symbolic computation, we obtain the lump, breather-wave and rogue-wave solutions under certain constraints. We graphically study the lump waves with the influence of the parameters h1, h3 and h5 which are all the real constants: When h1 increases, amplitude of the lump wave increases, and location of the peak moves; when h3 increases, lump wave’s amplitude decreases, but location of the peak keeps unchanged; when h5 changes, lump wave’s peak location moves, but amplitude keeps unchanged. Breather waves and rogue waves are displayed: Rogue waves emerge when the periods of the breather waves go to the infinity.

Approach to the diagnosis of a breast lump

African Journals Online (AJOL)

Generally, the older the woman, the greater the degree of suspicion and the more aggressive the ... When patients present with a history of a breast lump, the first crucial step is to ... A past history of a breast biopsy showing atypical hyperplasia, a family history of ... ultrasonography is the preferred modality for women under ...

QSAR models for the removal of organic micropollutants in four different river water matrices

KAUST Repository

Sudhakaran, Sairam; Calvin, James; Amy, Gary L.

2012-01-01

Ozonation is an advanced water treatment process used to remove organic micropollutants (OMPs) such as pharmaceuticals and personal care products (PPCPs). In this study, Quantitative Structure Activity Relationship (QSAR) models, for ozonation

Application of 3D-QSAR, Pharmacophore, and Molecular Docking in the Molecular Design of Diarylpyrimidine Derivatives as HIV-1 Nonnucleoside Reverse Transcriptase Inhibitors.

Science.gov (United States)

Liu, Genyan; Wang, Wenjie; Wan, Youlan; Ju, Xiulian; Gu, Shuangxi

2018-05-11

Diarylpyrimidines (DAPYs), acting as HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs), have been considered to be one of the most potent drug families in the fight against acquired immunodeficiency syndrome (AIDS). To better understand the structural requirements of HIV-1 NNRTIs, three-dimensional quantitative structure⁻activity relationship (3D-QSAR), pharmacophore, and molecular docking studies were performed on 52 DAPY analogues that were synthesized in our previous studies. The internal and external validation parameters indicated that the generated 3D-QSAR models, including comparative molecular field analysis (CoMFA, q 2 = 0.679, R 2 = 0.983, and r pred 2 = 0.884) and comparative molecular similarity indices analysis (CoMSIA, q 2 = 0.734, R 2 = 0.985, and r pred 2 = 0.891), exhibited good predictive abilities and significant statistical reliability. The docking results demonstrated that the phenyl ring at the C₄-position of the pyrimidine ring was better than the cycloalkanes for the activity, as the phenyl group was able to participate in π⁻π stacking interactions with the aromatic residues of the binding site, whereas the cycloalkanes were not. The pharmacophore model and 3D-QSAR contour maps provided significant insights into the key structural features of DAPYs that were responsible for the activity. On the basis of the obtained information, a series of novel DAPY analogues of HIV-1 NNRTIs with potentially higher predicted activity was designed. This work might provide useful information for guiding the rational design of potential HIV-1 NNRTI DAPYs.

QSAR models for prediction of chromatographic behavior of homologous Fab variants.

Science.gov (United States)

Robinson, Julie R; Karkov, Hanne S; Woo, James A; Krogh, Berit O; Cramer, Steven M

2017-06-01

While quantitative structure activity relationship (QSAR) models have been employed successfully for the prediction of small model protein chromatographic behavior, there have been few reports to date on the use of this methodology for larger, more complex proteins. Recently our group generated focused libraries of antibody Fab fragment variants with different combinations of surface hydrophobicities and electrostatic potentials, and demonstrated that the unique selectivities of multimodal resins can be exploited to separate these Fab variants. In this work, results from linear salt gradient experiments with these Fabs were employed to develop QSAR models for six chromatographic systems, including multimodal (Capto MMC, Nuvia cPrime, and two novel ligand prototypes), hydrophobic interaction chromatography (HIC; Capto Phenyl), and cation exchange (CEX; CM Sepharose FF) resins. The models utilized newly developed "local descriptors" to quantify changes around point mutations in the Fab libraries as well as novel cluster descriptors recently introduced by our group. Subsequent rounds of feature selection and linearized machine learning algorithms were used to generate robust, well-validated models with high training set correlations (R 2  > 0.70) that were well suited for predicting elution salt concentrations in the various systems. The developed models then were used to predict the retention of a deamidated Fab and isotype variants, with varying success. The results represent the first successful utilization of QSAR for the prediction of chromatographic behavior of complex proteins such as Fab fragments in multimodal chromatographic systems. The framework presented here can be employed to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives. Biotechnol. Bioeng. 2017;114: 1231-1240. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

Science.gov (United States)

Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-06-15

The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

The Interplay between QSAR/QSPR Studiesand Partial Order Ranking and Formal Concept Analyses

Directory of Open Access Journals (Sweden)

Lars Carlsen

2009-04-01

Full Text Available The often observed scarcity of physical-chemical and well as toxicological data hampers the assessment of potentially hazardous chemicals released to the environment. In such cases Quantitative Structure-Activity Relationships/Quantitative Structure-Property Relationships (QSAR/QSPR constitute an obvious alternative for rapidly, effectively and inexpensively generatng missing experimental values. However, typically further treatment of the data appears necessary, e.g., to elucidate the possible relations between the single compounds as well as implications and associations between the various parameters used for the combined characterization of the compounds under investigation. In the present paper the application of QSAR/QSPR in combination with Partial Order Ranking (POR methodologies will be reviewed and new aspects using Formal Concept Analysis (FCA will be introduced. Where POR constitutes an attractive method for, e.g., prioritizing a series of chemical substances based on a simultaneous inclusion of a range of parameters, FCA gives important information on the implications associations between the parameters. The combined approach thus constitutes an attractive method to a preliminary assessment of the impact on environmental and human health by primary pollutants or possibly by a primary pollutant well as a possible suite of transformation subsequent products that may be both persistent in and bioaccumulating and toxic.The present review focus on the environmental – and human health impact by residuals of the rocket fuel 1,1-dimethyl- hydrazine (heptyl and its transformation products as an illustrative example.

29 CFR 4044.75 - Other lump sum benefits.

Science.gov (United States)

2010-07-01

... sum benefits. The value of a lump sum benefit which is not covered under § 4044.73 or § 4044.74 is equal to— (a) The value under the qualifying bid, if an insurer provides the benefit; or (b) The present value of the benefit as of the date of distribution, determined using reasonable actuarial assumptions...

Leaks, Lumps, and Lines: Stigma and Women's Bodies

Science.gov (United States)

Chrisler, Joan C.

2011-01-01

Women's bodies have often been positioned in art and popular culture as monstrous or defiled and women's bodily products (e.g., menstrual fluid, breast milk) as disgusting. This framing has led to the stigmatization of aspects of women's bodies (e.g., leaking fluids, lumps of fat, and lines in the skin that indicate aging), especially those…

A stepwise approach for defining the applicability domain of SAR and QSAR models

DEFF Research Database (Denmark)

Dimitrov, Sabcho; Dimitrova, Gergana; Pavlov, Todor

2005-01-01

A stepwise approach for determining the model applicability domain is proposed. Four stages are applied to account for the diversity and complexity of the current SAR/QSAR models, reflecting their mechanistic rationality (including metabolic activation of chemicals) and transparency. General para...

Comparison of the AWA lumped-circuit model of electrical discharges with empirical data

International Nuclear Information System (INIS)

Maier, W.B. II; Kadish, A.; Robiscoe, R.T.

1990-01-01

The authors compare experimental data for three 1.7-m-long transient discharges with an AWA lumped- circuit discharge model in which the arc resistance is taken from the Arc Welder's Ansatz, R a = V*/|I |, where V* is a positive constant and I is the discharge current. In addition to the arc resistance, there is a small series resistance R present in the external circuit. A single value for each of R and V* is deduced from the data, and these values are used to characterize all three discharges. Adequate agreement with the experimental data is obtained; for example, the authors predict the proper number of current reversals for each discharge and abrupt termination of current flow after a finite time. The authors suggest that the AWA lumped circuit provides a better representation of the data than a standard lumped-circuit RLC model and hence is more useful as a tool for prediction and interpretation of discharges

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

Science.gov (United States)

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

A 3D Lumped Thermal Network Model for Long-term Load Profiles Analysis in High Power IGBT Modules

DEFF Research Database (Denmark)

Bahman, Amir Sajjad; Ma, Ke; Ghimire, Pramod

2016-01-01

)-based simulation is another method which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel...... enables both accurate and fast temperature estimation of high power IGBT modules in the real loading conditions of the converter; meanwhile the critical details of the thermal dynamics and thermal distribution are also maintained. The proposed thermal model is verified by both FEM simulation......The conventional RC lumped thermal networks are widely used to estimate the temperature of power devices, but they are lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high power IGBT modules. On the other hand, Finite Element (FE...

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

Science.gov (United States)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Synthesis, characterization, crystal structures, QSAR study and antibacterial activities of organotin bisphosphoramidates

Czech Academy of Sciences Publication Activity Database

Gholivand, K.; Valmoozi, A.A.E.; Gholami, A.; Dušek, Michal; Eigner, Václav; Abolghasemi, S.

2016-01-01

Roč. 806, Mar (2016), s. 33-44 ISSN 0022-328X R&D Projects: GA ČR GA15-12653S Institutional support: RVO:68378271 Keywords : bisphosphoramidate * organotin compounds * crystal structure * antibacterial activity * QSAR Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.184, year: 2016

2D QSAR studies of the inhibitory activity of a series of substituted purine derivatives against c-Src tyrosine kinase

OpenAIRE

Mukesh C. Sharma

2016-01-01

A series of 34 substituted purine analogues derivatives were subjected to quantitative structure-activity relationship analyses as inhibitors of c-Src tyrosine kinase. Partial least squares regression was applied to derive QSAR models, which were further validated for statistical significance by internal and external validation. The best QSAR model developed had a good predictive correlation coefficient (r2) of 0.8319, a significant cross-validated correlation coefficient (q2) of 0.7550, and ...

Importance theory for lumped-parameter systems

International Nuclear Information System (INIS)

Cady, K.B.; Kenton, M.A.; Ward, J.C.; Piepho, M.G.

1981-01-01

A general sensitivity theory has been developed for nonlinear lumped parameter system simulations. The point of departure is general perturbation theory for nonlinear systems. Importance theory as developed here allows the calculation of the sensitivity of a response function to any physical or design parameter; importance of any equation or term or physical effect in the system model on the response function; variance of the response function caused by the variances and covariances of all physical parameters; and approximate effect on the response function of missing physical phenomena or incorrect parameters

QSAR models for predicting in vivo aquatic toxicity of chlorinated alkanes to fish

NARCIS (Netherlands)

Zvinavashe, E.; Berg, H. van den; Soffers, A.E.M.F.; Vervoort, J.; Freidig, A.; Murk, A.J.; Rietjens, I.M.C.M.

2008-01-01

Quantitative structure-activity relationship (QSAR) models are expected to play a crucial role in reducing the number of animals to be used for toxicity testing resulting from the adoption of the new European Union chemical control system called Registration, Evaluation, and Authorization of

Some error estimates for the lumped mass finite element method for a parabolic problem

KAUST Repository

Chatzipantelidis, P.

2012-01-01

We study the spatially semidiscrete lumped mass method for the model homogeneous heat equation with homogeneous Dirichlet boundary conditions. Improving earlier results we show that known optimal order smooth initial data error estimates for the standard Galerkin method carry over to the lumped mass method whereas nonsmooth initial data estimates require special assumptions on the triangulation. We also discuss the application to time discretization by the backward Euler and Crank-Nicolson methods. © 2011 American Mathematical Society.

QSAR models for reproductive toxicity and endocrine disruption in regulatory use - a preliminary investigation

DEFF Research Database (Denmark)

Jensen, Gunde Egeskov; Niemela, J.R.; Wedebye, Eva Bay

2008-01-01

A special challenge in the new European Union chemicals legislation, Registration, Evaluation and Authorisation of Chemicals, will be the toxicological evaluation of chemicals for reproductive toxicity. Use of valid quantitative structure-activity relationships (QSARs) is a possibility under...

lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models

Science.gov (United States)

Pilz, Tobias; Francke, Till; Bronstert, Axel

2017-08-01

The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all. Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes.

Analysis of stability and bifurcations of fixed points and periodic solutions of a lumped model of neocortex with two delays

NARCIS (Netherlands)

Visser, Sid; Meijer, Hil G.E.; van Putten, Michel J.A.M.; van Gils, Stephan A.

2012-01-01

A lumped model of neural activity in neocortex is studied to identify regions of multi-stability of both steady states and periodic solutions. Presence of both steady states and periodic solutions is considered to correspond with epileptogenesis. The model, which consists of two delay differential

Aggressive angiomyxoma presenting with huge abdominal lump: A case report

Science.gov (United States)

Kumar, Sanjeev; Agrawal, Nikhil; Khanna, Rahul; Khanna, AK

2008-01-01

Agressive angiomyxoma is a rare mesenchymal neoplasm. It mainly presents in females. We here present a case of angiomyxoma presenting as huge abdominal lump along with gluteal swelling. Case note is described along with brief review of literature. PMID:18755035

QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

Science.gov (United States)

Alves, Vinicius M.; Capuzzi, Stephen J.; Muratov, Eugene; Braga, Rodolpho C.; Thornton, Thomas; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2016-01-01

Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher CCR of 82% but at the expense of the reduced external dataset coverage (52%). We used the developed QSAR models for virtual screening of CosIng database and identified 1061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential. PMID:28630595

Incidence data for breast cancer among Yemeni female patients with palpable breast lumps.

Science.gov (United States)

Alsanabani, Jamila Ali; Gilan, Waleed; Saadi, Azzan Al

2015-01-01

To estimate the incidence of breast cancer in Yemeni female patients presenting with a breast mass. This retrospective study was carried out with 595 female patients with palpable breast lumps, attending to Alkuwait university hospital, Sana'a, Yemen. Triple assessment, including breast examination, mammography and biopsy (FNAC, core needle, or excision), for all patients were performed. The incidences of benign and malignant lesions was calculated. Some 160 (26.9%) of 595 patients had malignancies; 213 (35.8%) were fibroadenomas; 12 (2.0%) were fibrocystic change; 143 (24.03%) were inflammatory lesions (including mastitis and ductectasia); 62 (10.4%) were simple cysts, while 5 (0.8%) were phyllodes tumors. The mean age of patients with malignant lumps was 44.3 years. Among Yemeni female patients with palpable breast lumps, the rate of breast cancer is high, with occurrence at an earlier age than in Western countries. Improving breast cancer awareness programs and increasing breast cancer screening centers inb different areas of Yemen are needed to establish early diagnosis and offer early and optimal treatment.

3D-QSAR, molecular docking, and molecular dynamic simulations for prediction of new Hsp90 inhibitors based on isoxazole scaffold.

Science.gov (United States)

Abbasi, Maryam; Sadeghi-Aliabadi, Hojjat; Amanlou, Massoud

2018-05-01

Heat shock protein 90(Hsp90), as a molecular chaperone, play a crucial role in folding and proper function of many proteins. Hsp90 inhibitors containing isoxazole scaffold are currently being used in the treatment of cancer as tumor suppressers. Here in the present studies, new compounds based on isoxazole scaffold were predicted using a combination of molecular modeling techniques including three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamic (MD) simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were also done. The steric and electrostatic contour map of CoMFA and CoMSIA were created. Hydrophobic, hydrogen bond donor and acceptor of CoMSIA model also were generated, and new compounds were predicted by CoMFA and CoMSIA contour maps. To investigate the binding modes of the predicted compounds in the active site of Hsp90, a molecular docking simulation was carried out. MD simulations were also conducted to evaluate the obtained results on the best predicted compound and the best reported Hsp90 inhibitors in the 3D-QSAR model. Findings indicate that the predicted ligands were stable in the active site of Hsp90.

Lump Sum Moving Cost and Aggregate Office Space Use

NARCIS (Netherlands)

G. Romijn

1997-01-01

textabstractWhen firms decide to change office space use, in many instances this involves relocation. Relocation involves sizable costs to the firm that can to a large extent be characterized as lump sum, i.e. independent of the change in demand. In this paper we propose and solve a model of the

QSAR Modeling and Prediction of Drug-Drug Interactions.

Science.gov (United States)

Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Primary Breast Tuberculosis Presenting as a Lump: A Rare Modern ...

African Journals Online (AJOL)

mammary area. A 25. year.old female, presented with a lump in the breast and infra.mammary area. She was having off and on fever without any other complaints. There was no positive family history. Primary breast tuberculosis was diagnosed on fine ...

GEYSER/TONUS: a coupled multi-D lumped parameter code for reactor thermal hydraulics analysis in case of severe accidents

Energy Technology Data Exchange (ETDEWEB)

Petit, M.; Durin, M.; Gauvain, J.

1995-12-31

The safety requirements for future light water reactors include accounting for severe accidents in the design process. The design must now include mitigation features to limit pressure and temperature inside the building. Hydrogen concentration is also a major issue for severe accidents. Modelling the thermal hydraulics inside the containment requires the description of complex phenomena such as condensation, stratification, transport of gases and aerosols, heat transfers. The effect of mitigation systems will increase the heterogeneities in the building, and most of those phenomena can be coupled. The GEYSER/TONUS multi-dimensional computer code is under development at CEA Saclay to model this complex situation. It allow the coupling of parts of the containment described in a lumped parameter manner, together with meshed parts. Emphasis is put on the numerical methods used to solve the transient problem, and physical models of classical lumped parameters codes will be adapted for the spatially described zones. The code is developed in the environment of the CASTEM 2000/TRIO EF system which allows to construct sophisticated applications based upon it. (J.S.). 22 refs., 1 fig.

GEYSER/TONUS: a coupled multi-D lumped parameter code for reactor thermal hydraulics analysis in case of severe accidents

International Nuclear Information System (INIS)

Petit, M.; Durin, M.; Gauvain, J.

1995-01-01

The safety requirements for future light water reactors include accounting for severe accidents in the design process. The design must now include mitigation features to limit pressure and temperature inside the building. Hydrogen concentration is also a major issue for severe accidents. Modelling the thermal hydraulics inside the containment requires the description of complex phenomena such as condensation, stratification, transport of gases and aerosols, heat transfers. The effect of mitigation systems will increase the heterogeneities in the building, and most of those phenomena can be coupled. The GEYSER/TONUS multi-dimensional computer code is under development at CEA Saclay to model this complex situation. It allow the coupling of parts of the containment described in a lumped parameter manner, together with meshed parts. Emphasis is put on the numerical methods used to solve the transient problem, and physical models of classical lumped parameters codes will be adapted for the spatially described zones. The code is developed in the environment of the CASTEM 2000/TRIO EF system which allows to construct sophisticated applications based upon it. (J.S.). 22 refs., 1 fig

Insights on Cytochrome P450 Enzymes and Inhibitors Obtained Through QSAR Studies

Directory of Open Access Journals (Sweden)

Maryam Foroozesh

2012-08-01

Full Text Available The cytochrome P450 (CYP superfamily of heme enzymes play an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. Inhibitors of CYP enzymes have important roles in the treatment of several disease conditions such as numerous cancers and fungal infections in addition to their critical role in drug-drug interactions. Structure activity relationships (SAR, and three-dimensional quantitative structure activity relationships (3D-QSAR represent important tools in understanding the interactions of the inhibitors with the active sites of the CYP enzymes. A comprehensive account of the QSAR studies on the major human CYPs 1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4 and a few other CYPs are detailed in this review which will provide us with an insight into the individual/common characteristics of the active sites of these enzymes and the enzyme-inhibitor interactions.

Do Lumped-Parameter Models Provide the Correct Geometrical Damping?

DEFF Research Database (Denmark)

Andersen, Lars

response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

Science.gov (United States)

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R2=0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q2ext = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. PMID:25560673

Start-up of belt conveyors used for haulage of large lumps under difficult climatic conditions

Energy Technology Data Exchange (ETDEWEB)

Drobny, J

1979-01-01

Investigations are discussed carried out by the Research and Development Center for Brown Coal in Most, Czechoslovakia into effects of climate, weather and mass of coal lumps on reliability of belt conveyors in surface mines. Dirt buildup on the driving drums reduces friction and increases belt sliding hazards. Belt wear increases. Driving drum diameter, increased by the buildup, negatively influences load distribution among the electric motors of the drive system. In extreme cases belt wear and irregular load distribution cause belt failures. Methods for buildup removal used in Czechoslovakia and methods for protection of the return side of a conveyor are described. Effects of large mass of coal lumps and ice buildup on large lumps on the risk of belt damage (cuts, punctures etc,) are discussed. Recommendations for design of coal transfer points are made. 2 refs.

Consensus hologram QSAR modeling for the prediction of human intestinal absorption.

Science.gov (United States)

Moda, Tiago L; Andricopulo, Adriano D

2012-04-15

Consistent in silico models for ADME properties are useful tools in early drug discovery. Here, we report the hologram QSAR modeling of human intestinal absorption using a dataset of 638 compounds with experimental data associated. The final validated models are consistent and robust for the consensus prediction of this important pharmacokinetic property and are suitable for virtual screening applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

20 CFR 725.521 - Commutation of payments; lump sum awards.

Science.gov (United States)

2010-04-01

... present value of future benefit payments commuted, computed at 4 percent true discount compounded annually... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Commutation of payments; lump sum awards. 725.521 Section 725.521 Employees' Benefits EMPLOYMENT STANDARDS ADMINISTRATION, DEPARTMENT OF LABOR...

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

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

Science.gov (United States)

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

2008-06-01

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

Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking

Directory of Open Access Journals (Sweden)

Guohui Sun

2016-06-01

Full Text Available DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT, which plays an important role in inducing drug resistance against alkylating agents that modify the O6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O6-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv2 = 0.672 and Rncv2 = 0.997 and CoMSIA (Qcv2 = 0.703 and Rncv2 = 0.946 models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext2 = 0.691, Rpred2 = 0.738 and slope k = 0.91 was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext2 = 0.307, Rpred2 = 0.4 and slope k = 0.719. Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

QSAR Studies of 6-Amino Uracil Base Analogues: A Thymidine Phosphorylase Inhibitor in Cancer Therapy

Directory of Open Access Journals (Sweden)

Surya Prakash B. N. Gupta

2008-01-01

Full Text Available A novel series of 6-amino uracil base analogue were synthesized. QSAR study was used to relate the selective nonsubstrate inhibitory activity of 6-amino uracil base analogue with various physicochemical descriptors. Stepwise multiple regression analysis was performed to find out the correlation between various physicochemical descriptors and biological activity of the compounds by using Openstat 2 version 6.5.1 and valstat statistical software. Out of the several equations developed, the best equation having the highest significance was selected for further study. The equation is able to explain 60% of total variance and are more than 95% significant as revealed by the F value.

Quantitative structure activity relationships (QSAR) for binary mixtures at non-equitoxic ratios based on toxic ratios-effects curves.

Science.gov (United States)

Tian, Dayong; Lin, Zhifen; Yin, Daqiang

2013-01-01

The present study proposed a QSAR model to predict joint effects at non-equitoxic ratios for binary mixtures containing reactive toxicants, cyanogenic compounds and aldehydes. Toxicity of single and binary mixtures was measured by quantifying the decrease in light emission from the Photobacterium phosphoreum for 15 min. The joint effects of binary mixtures (TU sum) can thus be obtained. The results showed that the relationships between toxic ratios of the individual chemicals and their joint effects can be described by normal distribution function. Based on normal distribution equations, the joint effects of binary mixtures at non-equitoxic ratios ( [Formula: see text]) can be predicted quantitatively using the joint effects at equitoxic ratios ( [Formula: see text]). Combined with a QSAR model of [Formula: see text]in our previous work, a novel QSAR model can be proposed to predict the joint effects of mixtures at non-equitoxic ratios ( [Formula: see text]). The proposed model has been validated using additional mixtures other than the one used for the development of the model. Predicted and observed results were similar (p>0.05). This study provides an approach to the prediction of joint effects for binary mixtures at non-equitoxic ratios.

QSAR models for anti-androgenic effect - a preliminary study

DEFF Research Database (Denmark)

Jensen, Gunde Egeskov; Nikolov, Nikolai Georgiev; Wedebye, Eva Bay

2011-01-01

Three modelling systems (MultiCase (R), LeadScope (R) and MDL (R) QSAR) were used for construction of androgenic receptor antagonist models. There were 923-942 chemicals in the training sets. The models were cross-validated (leave-groups-out) with concordances of 77-81%, specificity of 78...... of the model for a particular application, balance of training sets, domain definition, and cut-offs for prediction interpretation should also be taken into account. Different descriptors in the modelling systems are illustrated with hydroxyflutamide and dexamethasone as examples (a non-steroid and a steroid...

Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

Science.gov (United States)

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external dataset, the best way to validate the predictive ability of a model is to perform its s...

Scattering of massless lumps and non-local charges in the two-dimensional classical non-linear sigma-model

International Nuclear Information System (INIS)

Luescher, M.; Pohlmeyer, K.

1977-09-01

Finite energy solutions of the field equations of the non-linear sigma-model are shown to decay asymptotically into massless lumps. By means of a linear eigenvalue problem connected with the field equations we then find an infinite set of dynamical conserved charges. They, however, do not provide sufficient information to decode the complicated scattering of lumps. (orig.) [de

A Calibrated Lumped Element Model for the Prediction of PSJ Actuator Efficiency Performance

Directory of Open Access Journals (Sweden)

Matteo Chiatto

2018-03-01

Full Text Available Among the various active flow control techniques, Plasma Synthetic Jet (PSJ actuators, or Sparkjets, represent a very promising technology, especially because of their high velocities and short response times. A practical tool, employed for design and manufacturing purposes, consists of the definition of a low-order model, lumped element model (LEM, which is able to predict the dynamic response of the actuator in a relatively quick way and with reasonable fidelity and accuracy. After a brief description of an innovative lumped model, this work faces the experimental investigation of a home-designed and manufactured PSJ actuator, for different frequencies and energy discharges. Particular attention has been taken in the power supply system design. A specific home-made Pitot tube has allowed the detection of velocity profiles along the jet radial direction, for various energy discharges, as well as the tuning of the lumped model with experimental data, where the total device efficiency has been assumed as a fitting parameter. The best fitting value not only contains information on the actual device efficiency, but includes some modeling and experimental uncertainties, related also to the used measurement technique.

Steady And Unsteady Lumped-Parameter Models For Determination of Groundwater Residence Time Distribution

International Nuclear Information System (INIS)

Oezyurt, N.N.

2002-01-01

Groundwater's residence time distribution is an important information to identify the transport mechanism in aquifer systems. In the absence or scarcity of geometric, hydraulic and geohydrologic data needed to describe a flow system, lumped parameter models, that handle the flow system as a whole, exist as an alternative to determine the residence time distribution. Lumped parametre models comprise of idealized models of piston and well-mixed flow and their combinations. Aquifer properties such as, dead volume and by-pass flow can also be included in these models. With the aid of these models, conceptual aquifer models can be tested and residence time distribution of groundwater can be determined

New lumped-mass-stick model based on modal characteristics of structures: development and application to a nuclear containment building

Science.gov (United States)

Roh, Hwasung; Lee, Huseok; Lee, Jong Seh

2013-06-01

In this study, a new lumped-mass-stick model (LMSM) is developed based on the modal characteristics of a structure such as eigenvalues and eigenvectors. The simplified model, named the "frequency adaptive lumped-massstick model," hasonly a small number of stick elements and nodes to provide the same natural frequencies of the structure and is applied to a nuclear containment building. To investigate the numerical performance of the LMSM, a time history analysis is carried out on both the LMSM and the finite element model (FEM) for a nuclear containment building. A comparison of the results shows that the dynamic responses of the LMSM in terms of displacement and acceleration are almost identical to those of the FEM. In addition, the results in terms of fl oor response spectra at certain elevations are also in good agreement.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

International Nuclear Information System (INIS)

Valencia, Antoni; Prous, Josep; Mora, Oscar; Sadrieh, Nakissa; Valerio, Luis G.

2013-01-01

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90% was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests

Design and combinatorial library generation of 1H 1,4 benzodiazepine 2,5 diones as photosystem-II inhibitors: A public QSAR approach

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Purusottam Banjare

2017-09-01

Full Text Available Exponential rise in the population around the word increased the demand of food grains/crops with limited expansion of the agricultural land. To meet the demand, generation of new herbicidal agents is of primary need for the manufacturing firm. In silico tool like QSAR is one of the regularly used in designing newer compounds along with wet experiment. Photosystem-II (PS-II regarded as one of the major target for the herbicidal agents. With this aim in the present study a series of 1H, 1,4 benzodiazepine 2,5-dione analogues as herbicidal (PS-II inhibitors agents were subjected to QSAR analysis using 2D PaDEL descriptors (open source. Two different splitting techniques namely, kennard stone based and k-means clustering splitting were used to divide the whole data set and GFA based on MAE criteria was used a statistical method to develop a model to investigate the physicochemical and structural requirement of potential PS-II inhibitors. All the models are statistically robust both internally and externally (Q2: 0.540–0.693, R2pred: 0.722–0.810. The activity is mostly affected by polarizabilities, electro negativities as well as substituents at the phenyl ring. Based on the results, a library of compounds was generated using SmiLib v2.0 tool (open source and better predicted inside applicability domain compounds were identified by applying three different applicability domain (AD approaches. Therefore the developed public QSAR models may be helpful for the scientific community for the further research.

Lumped elements for RF and microwave circuits

CERN Document Server

Bahl, Inder

2003-01-01

Due to the unprecedented growth in wireless applications over the past decade, development of low-cost solutions for RF and microwave communication systems has become of great importance. This practical new book is the first comprehensive treatment of lumped elements, which are playing a critical role in the development of the circuits that make these cost-effective systems possible. The books offers you an in-depth understanding of the different types of RF and microwave circuit elements, including inductors, capacitors, resistors, transformers, via holes, airbridges, and crossovers. Support

QSAR studies of some side chain modified 7-chloro-4-aminoquinolines as antimalarial agents

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Nitendra K. Sahu

2014-11-01

Full Text Available The quantitative structure–activity relationship (QSAR analyses were carried out for a series of new side chain modified 4-amino-7-chloroquinolines to find out the structural requirements of their antimalarial activities against both chloroquine sensitive (HB3 and resistant (Dd2 Plasmodium falciparum strain. The statistically significant best 2D QSAR models for Dd2, having correlation coefficient (r2 = 0.9188 and cross validated squared correlation coefficient (q2 = 0.8349 with external predictive ability (pred_r2 = 0.7258 and for HB3, having r2 = 0.9024, q2 = 0.8089 and pred_r2 = 0.7463 were developed by multiple linear regression coupled with genetic algorithm (GA–MLR and stepwise (SW–MLR forward algorithm, respectively. The results of the present study may be useful on the designing of more potent analogues as antimalarial agents.

Development of human biotransformation QSARs and application for PBT assessment refinement.

Science.gov (United States)

Papa, Ester; Sangion, Alessandro; Arnot, Jon A; Gramatica, Paola

2018-02-01

Toxicokinetics heavily influence chemical toxicity as the result of Absorption, Distribution, Metabolism (Biotransformation) and Elimination (ADME) processes. Biotransformation (metabolism) reactions can lead to detoxification or, in some cases, bioactivation of parent compounds to more toxic chemicals. Moreover, biotransformation has been recognized as a key process determining chemical half-life in an organism and is thus a key determinant for bioaccumulation assessment for many chemicals. This study addresses the development of QSAR models for the prediction of in vivo whole body human biotransformation (metabolism) half-lives measured or empirically-derived for over 1000 chemicals, mainly represented by pharmaceuticals. Models presented in this study meet regulatory standards for fitting, validation and applicability domain. These QSARs were used, in combination with literature models for the prediction of biotransformation half-lives in fish, to refine the screening of the potential PBT behaviour of over 1300 Pharmaceuticals and Personal Care Products (PPCPs). The refinement of the PBT screening allowed, among others, for the identification of PPCPs, which were predicted as PBTs on the basis of their chemical structure, but may be easily biotransformed. These compounds are of lower concern in comparison to potential PBTs characterized by large predicted biotransformation half-lives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Novel 3-Amino-6-chloro-7-(azol-2 or 5-yl-1,1-dioxo-1,4,2-benzodithiazine Derivatives with Anticancer Activity: Synthesis and QSAR Study

Directory of Open Access Journals (Sweden)

Aneta Pogorzelska

2015-12-01

Full Text Available A series of new 3-amino-6-chloro-7-(azol-2 or 5-yl-1,1-dioxo-1,4,2-benzodithiazine derivatives 5a–j have been synthesized and evaluated in vitro for their antiproliferative activity at the U.S. National Cancer Institute. The most active compound 5h showed significant cytotoxic effects against ovarian (OVCAR-3 and breast (MDA-MB-468 cancer (10% and 47% cancer cell death, respectively as well as a good selectivity toward prostate (DU-145, colon (SW-620 and renal (TK-10 cancer cell lines. To obtain a deeper insight into the structure-activity relationships of the new compounds 5a–j QSAR studies have been applied. Theoretical calculations allowed the identification of molecular descriptors belonging to the RDF (RDF055p and RDF145m in the MOLT-4 and UO-31 QSAR models, respectively and 3D-MorSE (Mor32m and Mor16e for MOLT-4 and UO-31 QSAR models descriptor classes. Based on these data, QSAR models with good robustness and predictive ability have been obtained.

Deducing Electronic Unit Internal Response During a Vibration Test Using a Lumped Parameter Modeling Approach

Science.gov (United States)

Van Dyke, Michael B.

2014-01-01

During random vibration testing of electronic boxes there is often a desire to know the dynamic response of certain internal printed wiring boards (PWBs) for the purpose of monitoring the response of sensitive hardware or for post-test forensic analysis in support of anomaly investigation. Due to restrictions on internally mounted accelerometers for most flight hardware there is usually no means to empirically observe the internal dynamics of the unit, so one must resort to crude and highly uncertain approximations. One common practice is to apply Miles Equation, which does not account for the coupled response of the board in the chassis, resulting in significant over- or under-prediction. This paper explores the application of simple multiple-degree-of-freedom lumped parameter modeling to predict the coupled random vibration response of the PWBs in their fundamental modes of vibration. A simple tool using this approach could be used during or following a random vibration test to interpret vibration test data from a single external chassis measurement to deduce internal board dynamics by means of a rapid correlation analysis. Such a tool might also be useful in early design stages as a supplemental analysis to a more detailed finite element analysis to quickly prototype and analyze the dynamics of various design iterations. After developing the theoretical basis, a lumped parameter modeling approach is applied to an electronic unit for which both external and internal test vibration response measurements are available for direct comparison. Reasonable correlation of the results demonstrates the potential viability of such an approach. Further development of the preliminary approach presented in this paper will involve correlation with detailed finite element models and additional relevant test data.

QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

Science.gov (United States)

Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Novel T-Fed 4-Element Quasi-Lumped Resonator Antenna Array

Directory of Open Access Journals (Sweden)

S.S. Olokede

2014-06-01

Full Text Available In this paper, electrically small corporately T-fed quasi-lumped element resonator antenna array is investigated. The radiating element, a quasi-lumped element resonator is excited by a novel semi hybrid ring-like T-shaped corporate feed network. The characteristics losses due to Ohmic and discontinuities along the feed line which invariably constitutes complex feed structures are mitigated at the instance of the proposed antenna. Technique to implement the compact array with the intent to enhance the gain is presented. The operation dynamics of the feed along with its theoretical explanation is also reported. Findings indicates that the measured gain is 10.97 dBi for antenna of an estate area of about 0.677λ_0 × 1.257λ_0 sq. mm. Valuable insight to the optimum design in terms of compactness, good gain, and ease of fabrication is documented.

Method for Lumped Parameter simulation of Digital Displacement pumps/motors based on CFD

DEFF Research Database (Denmark)

Rømer, Daniel; Johansen, Per; Pedersen, Henrik C.

2013-01-01

Digital displacement fluid power pumps/motors offers improved efficiency and performance compared to traditional variable displacement pump/motors. These improvements are made possible by using efficient electronically controlled seat valves and careful design of the flow geometry. To optimize...... the design and control of digital displacement machines, there is a need for simulation models, preferably models with low computational cost. Therefore, a low computational cost generic lumped parameter model of digital displacement machine is presented, including a method for determining the needed model...... parameters based on steady CFD results, in order to take detailed geometry information into account. The response of the lumped parameter model is compared to a computational expensive transient CFD model for an example geometry....

Molecular docking, QSAR and ADMET based mining of natural compounds against prime targets of HIV.

Science.gov (United States)

Vora, Jaykant; Patel, Shivani; Sinha, Sonam; Sharma, Sonal; Srivastava, Anshu; Chhabria, Mahesh; Shrivastava, Neeta

2018-01-07

AIDS is one of the multifaceted diseases and this underlying complexity hampers its complete cure. The toxicity of existing drugs and emergence of multidrug-resistant virus makes the treatment worse. Development of effective, safe and low-cost anti-HIV drugs is among the top global priority. Exploration of natural resources may give ray of hope to develop new anti-HIV leads. Among the various therapeutic targets for HIV treatment, reverse transcriptase, protease, integrase, GP120, and ribonuclease are the prime focus. In the present study, we predicted potential plant-derived natural molecules for HIV treatment using computational approach, i.e. molecular docking, quantitative structure activity relationship (QSAR), and ADMET studies. Receptor-ligand binding studies were performed using three different software for precise prediction - Discovery studio 4.0, Schrodinger and Molegrow virtual docker. Docking scores revealed that Mulberrosides, Anolignans, Curcumin and Chebulic acid are promising candidates that bind with multi targets of HIV, while Neo-andrographolide, Nimbolide and Punigluconin were target-specific candidates. Subsequently, QSAR was performed using biologically proved compounds which predicted the biological activity of compounds. We identified Anolignans, Curcumin, Mulberrosides, Chebulic acid and Neo-andrographolide as potential natural molecules for HIV treatment from results of molecular docking and 3D-QSAR. In silico ADMET studies showed drug-likeness of these lead molecules. Structure similarities of identified lead molecules were compared with identified marketed drugs by superimposing both the molecules. Using in silico studies, we have identified few best fit molecules of natural origin against identified targets which may give new drugs to combat HIV infection after wet lab validation.

Advantages and disadvantages of lumping together gastroesophageal reflux disease and dyspepsia

NARCIS (Netherlands)

Smout, André J. P. M.

2006-01-01

PURPOSE OF REVIEW: The aim of this article is to identify and to balance the arguments in favor of and against lumping together gastroesophageal reflux disease and functional dyspepsia. RECENT FINDINGS: In at least half of the patients diagnosed with gastroesophageal reflux disease no organic

Definition of datum of materials lump size on conveyors by means of reflected gamma-radiation method

International Nuclear Information System (INIS)

Gal'yanov, A.V.; Antonov, V.A.; Laptev, Yu.V.

2001-01-01

A method of technological control of large-size lumps in conveyor-transported crushed material based on intensity measurement of X-ray and gamma radiation reflected from the material surface was suggested. The method was substantiated theoretically and as a result it was shown that dispersion of radiation intensity, multiply measured for short periods of time, can be analytic parameter of large-size lumps yield. Principled methodical and design recommendations on the method practical applications are given [ru

Comparative study of aspiration and non-aspiration cytology of palpable breast lumps and correlation with histopathology

Directory of Open Access Journals (Sweden)

S Koirala

2014-09-01

Full Text Available Background: Breast lump is one of the most common presentations in surgical outpatient departments with anxiety regarding a possible malignancy. Hence a quick diagnosis of a lump in the breast is essential. Fine needle aspiration cytology is an ideal initial diagnostic modality in breast lumps. There is an alternative method of performing needle aspiration, known as fine needle capillary cytology where the specimen is obtained using just a needle without aspiration.Materials and Methods: This hospital-based cross sectional analytical study was carried out in Department of Pathology in National Academy of Medical Sciences, Bir Hospital for one year. The objective of this study was to compare aspiration and non-aspiration cytology of palpable breast lumps and correlation with histopathology.Results: The five criteria scored for each technique were background blood, amount of cellular material, cellular degeneration, cellular trauma and architectural preservation. Compared to fine needle aspiration cytology, fine needle capillary cytology yields less bloody smears with minimal degenerative changes and offers more diagnostically superior specimens. Fine needle aspiration cytology, on the other hand, gives a good yield of diagnostic material.Conclusion: Fine needle aspiration cytology and fine needle capillary cytology are quick, easy, safe and cost-effective techniques. . A high sensitivity and specificity of cytological diagnosis in this study proves that it is comparable to final histology report in its diagnostic efficiency. Thus, fine needle aspiration cytology is a very important preliminary diagnostic test in palpable breast lumps and the results show a high degree of correlation with the final histopathology report.DOI: http://dx.doi.org/10.3126/jpn.v4i8.11501 Journal of Pathology of Nepal; Vol.4,No. 8 (2014 639-643

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models.

Science.gov (United States)

Chen, Ying; Cai, Xiaoyu; Jiang, Long; Li, Yu

2016-02-01

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are

An integrated QSAR-PBK/D modelling approach for predicting detoxification and DNA adduct formation of 18 acyclic food-borne α,β-unsaturated aldehydes

Energy Technology Data Exchange (ETDEWEB)

Kiwamoto, R., E-mail: reiko.kiwamoto@wur.nl; Spenkelink, A.; Rietjens, I.M.C.M.; Punt, A.

2015-01-01

Acyclic α,β-unsaturated aldehydes present in food raise a concern because the α,β-unsaturated aldehyde moiety is considered a structural alert for genotoxicity. However, controversy remains on whether in vivo at realistic dietary exposure DNA adduct formation is significant. The aim of the present study was to develop physiologically based kinetic/dynamic (PBK/D) models to examine dose-dependent detoxification and DNA adduct formation of a group of 18 food-borne acyclic α,β-unsaturated aldehydes without 2- or 3-alkylation, and with no more than one conjugated double bond. Parameters for the PBK/D models were obtained using quantitative structure–activity relationships (QSARs) defined with a training set of six selected aldehydes. Using the QSARs, PBK/D models for the other 12 aldehydes were defined. Results revealed that DNA adduct formation in the liver increases with decreasing bulkiness of the molecule especially due to less efficient detoxification. 2-Propenal (acrolein) was identified to induce the highest DNA adduct levels. At realistic dietary intake, the predicted DNA adduct levels for all aldehydes were two orders of magnitude lower than endogenous background levels observed in disease free human liver, suggesting that for all 18 aldehydes DNA adduct formation is negligible at the relevant levels of dietary intake. The present study provides a proof of principle for the use of QSAR-based PBK/D modelling to facilitate group evaluations and read-across in risk assessment. - Highlights: • Physiologically based in silico models were made for 18 α,β-unsaturated aldehydes. • Kinetic parameters were determined by in vitro incubations and a QSAR approach. • DNA adduct formation was negligible at levels relevant for dietary intake. • The use of QSAR-based PBK/D modelling facilitates group evaluations and read-across.

New Procedure to Develop Lumped Kinetic Models for Heavy Fuel Oil Combustion

KAUST Repository

Han, Yunqing; Elbaz, Ayman M.; Roberts, William L.; Im, Hong G.

2016-01-01

A new procedure to develop accurate lumped kinetic models for complex fuels is proposed, and applied to the experimental data of the heavy fuel oil measured by thermogravimetry. The new procedure is based on the pseudocomponents representing

Recomputing Causality Assignments on Lumped Process Models When Adding New Simplification Assumptions

Directory of Open Access Journals (Sweden)

Antonio Belmonte

2018-04-01

Full Text Available This paper presents a new algorithm for the resolution of over-constrained lumped process systems, where partial differential equations of a continuous time and space model of the system are reduced into ordinary differential equations with a finite number of parameters and where the model equations outnumber the unknown model variables. Our proposal is aimed at the study and improvement of the algorithm proposed by Hangos-Szerkenyi-Tuza. This new algorithm improves the computational cost and solves some of the internal problems of the aforementioned algorithm in its original formulation. The proposed algorithm is based on parameter relaxation that can be modified easily. It retains the necessary information of the lumped process system to reduce the time cost after introducing changes during the system formulation. It also allows adjustment of the system formulations that change its differential index between simulations.

Investigation into adamantane-based M2 inhibitors with FB-QSAR.

Science.gov (United States)

Wei, Hang; Wang, Cheng-Hua; Du, Qi-Shi; Meng, Jianzong; Chou, Kuo-Chen

2009-07-01

Because of their high resistance rate to the existing drugs, influenza A viruses have become a threat to human beings. It is known that the replication of influenza A viruses needs a pH-gated proton channel, the so-called M2 channel. Therefore, to develop effective drugs against influenza A, the most logic strategy is to inhibit the M2 channel. Recently, the atomic structure of the M2 channel was determined by NMR spectroscopy (Schnell, J.R. and Chou, J.J., Nature, 2008, 451, 591-595). The high-resolution NMR structure has provided a solid basis for structure-based drug design approaches. In this study, a benchmark dataset has been constructed that contains 34 newly-developed adamantane-based M2 inhibitors and covers considerable structural diversities and wide range of bioactivities. Based on these compounds, an in-depth analysis was performed with the newly developed fragment-based quantitative structure-activity relationship (FB-QSAR) algorithm. The results thus obtained provide useful insights for dealing with the drug-resistant problem and designing effective adamantane-based antiflu drugs.

QSAR Study of Insecticides of Phthalamide Derivatives Using Multiple Linear Regression and Artificial Neural Network Methods

Directory of Open Access Journals (Sweden)

Adi Syahputra

2014-03-01

Full Text Available Quantitative structure activity relationship (QSAR for 21 insecticides of phthalamides containing hydrazone (PCH was studied using multiple linear regression (MLR, principle component regression (PCR and artificial neural network (ANN. Five descriptors were included in the model for MLR and ANN analysis, and five latent variables obtained from principle component analysis (PCA were used in PCR analysis. Calculation of descriptors was performed using semi-empirical PM6 method. ANN analysis was found to be superior statistical technique compared to the other methods and gave a good correlation between descriptors and activity (r2 = 0.84. Based on the obtained model, we have successfully designed some new insecticides with higher predicted activity than those of previously synthesized compounds, e.g.2-(decalinecarbamoyl-5-chloro-N’-((5-methylthiophen-2-ylmethylene benzohydrazide, 2-(decalinecarbamoyl-5-chloro-N’-((thiophen-2-yl-methylene benzohydrazide and 2-(decaline carbamoyl-N’-(4-fluorobenzylidene-5-chlorobenzohydrazide with predicted log LC50 of 1.640, 1.672, and 1.769 respectively.

Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

Science.gov (United States)

Dobchev, Dimitar; Karelson, Mati

2016-07-01

Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably, in the past two decades, ANNs have been used widely in the process of drug discovery. In this review, the authors discuss advantages and disadvantages of ANNs in drug discovery as incorporated into the quantitative structure-activity relationships (QSAR) framework. Furthermore, the authors examine the recent studies, which span over a broad area with various diseases in drug discovery. In addition, the authors attempt to answer the question about the expectations of the ANNs in drug discovery and discuss the trends in this field. The old pitfalls of overtraining and interpretability are still present with ANNs. However, despite these pitfalls, the authors believe that ANNs have likely met many of the expectations of researchers and are still considered as excellent tools for nonlinear data modeling in QSAR. It is likely that ANNs will continue to be used in drug development in the future.

Development of CAP code for nuclear power plant containment: Lumped model

Energy Technology Data Exchange (ETDEWEB)

Hong, Soon Joon, E-mail: sjhong90@fnctech.com [FNC Tech. Co. Ltd., Heungdeok 1 ro 13, Giheung-gu, Yongin-si, Gyeonggi-do 446-908 (Korea, Republic of); Choo, Yeon Joon; Hwang, Su Hyun; Lee, Byung Chul [FNC Tech. Co. Ltd., Heungdeok 1 ro 13, Giheung-gu, Yongin-si, Gyeonggi-do 446-908 (Korea, Republic of); Ha, Sang Jun [Central Research Institute, Korea Hydro & Nuclear Power Company, Ltd., 70, 1312-gil, Yuseong-daero, Yuseong-gu, Daejeon 305-343 (Korea, Republic of)

2015-09-15

Highlights: • State-of-art containment analysis code, CAP, has been developed. • CAP uses 3-field equations, water level oriented upwind scheme, local head model. • CAP has a function of linked calculation with reactor coolant system code. • CAP code assessments showed appropriate prediction capabilities. - Abstract: CAP (nuclear Containment Analysis Package) code has been developed in Korean nuclear society for the analysis of nuclear containment thermal hydraulic behaviors including pressure and temperature trends and hydrogen concentration. Lumped model of CAP code uses 2-phase, 3-field equations for fluid behaviors, and has appropriate constitutive equations, 1-dimensional heat conductor model, component models, trip and control models, and special process models. CAP can run in a standalone mode or a linked mode with a reactor coolant system analysis code. The linked mode enables the more realistic calculation of a containment response and is expected to be applicable to a more complicated advanced plant design calculation. CAP code assessments were carried out by gradual approaches: conceptual problems, fundamental phenomena, component and principal phenomena, experimental validation, and finally comparison with other code calculations on the base of important phenomena identifications. The assessments showed appropriate prediction capabilities of CAP.

Development of CAP code for nuclear power plant containment: Lumped model

International Nuclear Information System (INIS)

Hong, Soon Joon; Choo, Yeon Joon; Hwang, Su Hyun; Lee, Byung Chul; Ha, Sang Jun

2015-01-01

Highlights: • State-of-art containment analysis code, CAP, has been developed. • CAP uses 3-field equations, water level oriented upwind scheme, local head model. • CAP has a function of linked calculation with reactor coolant system code. • CAP code assessments showed appropriate prediction capabilities. - Abstract: CAP (nuclear Containment Analysis Package) code has been developed in Korean nuclear society for the analysis of nuclear containment thermal hydraulic behaviors including pressure and temperature trends and hydrogen concentration. Lumped model of CAP code uses 2-phase, 3-field equations for fluid behaviors, and has appropriate constitutive equations, 1-dimensional heat conductor model, component models, trip and control models, and special process models. CAP can run in a standalone mode or a linked mode with a reactor coolant system analysis code. The linked mode enables the more realistic calculation of a containment response and is expected to be applicable to a more complicated advanced plant design calculation. CAP code assessments were carried out by gradual approaches: conceptual problems, fundamental phenomena, component and principal phenomena, experimental validation, and finally comparison with other code calculations on the base of important phenomena identifications. The assessments showed appropriate prediction capabilities of CAP

Primary Breast Tuberculosis Presenting as a Lump: A Rare Modern ...

African Journals Online (AJOL)

A 25‑year‑old female presented with a painless lump in her right breast for 1 month duration. She gave history of low grade fever off and on for the last 2 weeks. There were no other complaints like weight loss, loss of appetite, and any cough. She was unmarried and there was no positive family history of breast tuberculosis.

Docking based 3d-QSAR studies applied at the BRAF inhibitors to understand the binding mechanism

International Nuclear Information System (INIS)

Mahmood, U.; Haq, Z.U.

2011-01-01

BRAF is a great therapeutic target in a wide variety of human cancers. It is the member of Ras Activating Factor (RAF) family of serine/throenine kinase. The mutated form of the BRAF has diverted all the attention towards itself because of increase severity and elevated kinase activity. The RAF signal transduction cascade is a conserved protein pathway that is involved in cell cycle progression and apoptosis. The ERK regulates phosphorylation of different proteins either in cytosol or in nucleus but disorders in ERK signaling pathway cause mutation in BRAF. This cascade in these cells may provide selection of mutated BRAF in which valine is substituted with glutamatic acid at position 600. This mutation occurs in activation loop. A number of inhibitors reported to target different members of RAF, some of them have potential to target the BRAF as well. Major reason for failure of previously reported inhibitors was due to the highly conserved sequence and confirmation of catalytic cleft which is always a center of consideration for binding of inhibitors to suppress the kinase activity. This is the first attempt to study and understand the BARF inhibitors - protein interactions in detail by utilizing 3D-QSAR and molecular docking techniques. Most reliable techniques of 3D QSAR i.e Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied for three different data sets. The data sets selected for better evaluation of BRAF inhibitors belongs to 2, 6-Disubstituted Pyrazine, Pyridoimidazolones and its derivatives. Our models would offer help to better understand the structure-activity relationships that exist for these classes of compounds and also facilitate the design of novel inhibitors with good chemical diversity. (Author)

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

Science.gov (United States)

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

QSARs for phenols and phenolates: oxidation potential as a predictor of reaction rate constants with photochemically produced oxidants.

Science.gov (United States)

Arnold, William A; Oueis, Yan; O'Connor, Meghan; Rinaman, Johanna E; Taggart, Miranda G; McCarthy, Rachel E; Foster, Kimberley A; Latch, Douglas E

2017-03-22

Quantitative structure-activity relationships (QSARs) for prediction of the reaction rate constants of phenols and phenolates with three photochemically produced oxidants, singlet oxygen, carbonate radical, and triplet excited state sensitizers/organic matter, are developed. The predictive variable is the one-electron oxidation potential (E 1 ), which is calculated for each species using density functional theory. The reaction rate constants are obtained from the literature, and for singlet oxygen, are augmented with new experimental data. Calculated E 1 values have a mean unsigned error compared to literature values of 0.04-0.06 V. For singlet oxygen, a single linear QSAR that includes both phenols and phenolates is developed that predicts experimental rate constants, on average, to within a factor of three. Predictions for only 6 out of 87 compounds are off by more than a factor of 10. A more limited data set for carbonate radical reactions with phenols and phenolates also gives a single linear QSAR with prediction of rate constant being accurate to within a factor of three. The data for the reactions of phenols with triplet state sensitizers demonstrate that two sensitizers, 2-acetonaphthone and methylene blue, most closely predict the reactivity trend of triplet excited state organic matter with phenols. Using sensitizers with stronger reduction potentials could lead to overestimation of rate constants and thus underestimation of phenolic pollutant persistence.

Eco-friendly synthesis, in vitro anti-proliferative evaluation, and 3D-QSAR analysis of a novel series of monocationic 2-aryl/heteroaryl-substituted 6-(2-imidazolinyl)benzothiazole mesylates.

Science.gov (United States)

Racané, Livio; Ptiček, Lucija; Sedić, Mirela; Grbčić, Petra; Kraljević Pavelić, Sandra; Bertoša, Branimir; Sović, Irena; Karminski-Zamola, Grace

2018-04-17

positively correlated with anti-proliferative activity, while compound's capability to accept H-bond was identified as a negatively correlated property. Comparison of molecular properties identified for different cell lines enabled assumptions about similarity of mode of action through which anti-proliferative activities against different cell lines are accomplished. Novel compounds that are predicted to have enhanced activities in comparison with herein presented ones were designed using 3D-QSAR analysis as guideline.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

Energy Technology Data Exchange (ETDEWEB)

Valencia, Antoni; Prous, Josep; Mora, Oscar [Prous Institute for Biomedical Research, Rambla de Catalunya, 135, 3-2, Barcelona 08008 (Spain); Sadrieh, Nakissa [Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993-0002 (United States); Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993-0002 (United States)

2013-12-15

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90% was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. �

Improved lumped models for transient combined convective and radiative cooling of a two-layer spherical fuel element

International Nuclear Information System (INIS)

Silva, Alice Cunha da; Su, Jian

2013-01-01

The High Temperature Gas cooled Reactor (HTGR) is a fourth generation thermal nuclear reactor, graphite-moderated and helium cooled. The HTGRs have important characteristics making essential the study of these reactors, as well as its fuel element. Examples of these are: high thermal efficiency,low operating costs and construction, passive safety attributes that allow implication of the respective plants. The Pebble Bed Modular Reactor (PBMR) is a HTGR with spherical fuel elements that named the reactor. This fuel element is composed by a particulate region with spherical inclusions, the fuel UO2 particles, dispersed in a graphite matrix and a convective heat transfer by Helium happens on the outer surface of the fuel element. In this work, the transient heat conduction in a spherical fuel element of a pebble-bed high temperature reactor was studied in a transient situation of combined convective and radiative cooling. Improved lumped parameter model was developed for the transient heat conduction in the two-layer composite sphere subjected to combined convective and radiative cooling. The improved lumped model was obtained through two-point Hermite approximations for integrals. Transient combined convective and radiative cooling of the two-layer spherical fuel element was analyzed to illustrate the applicability of the proposed lumped model, with respect to die rent values of the Biot number, the radiation-conduction parameter, the dimensionless thermal contact resistance, the dimensionless inner diameter and coating thickness, and the dimensionless thermal conductivity. It was shown by comparison with numerical solution of the original distributed parameter model that the improved lumped model, with H2,1/H1,1/H0,0 approximation yielded significant improvement of average temperature prediction over the classical lumped model. (author)

Cytological and Pathological Correlation of FNAC in Assessing Breast Lumps and Axillary Lymph Node Swellings in a Public Sector Hospital in India

Directory of Open Access Journals (Sweden)

Vasu Reddy Challa

2013-01-01

Full Text Available Background. Breast lumps have varied pathology, and there are different techniques to prove the diagnosis. The aim of the present study is to analyze the role of fine needle aspiration cytology (FNAC of the breast lesions at our center. Methods. We had retrospectively analysed 854 patients who underwent FNAC for primary breast lumps and 190 patients who underwent FNAC for an axillary lymph node in the year 2010. Results. Of 854 patients, histological correlation was available in 723 patients. The analysis was done for 812 patients as medical records were not available for 42 patients. FNAC was false negative in seven cases; 2 cases of phyllodes were reported as fibroadenoma, and 5 cases of carcinoma were diagnosed as atypical hyperplasia. The sensitivity, specificity, and false negative value of FNAC in diagnosing breast lumps were 99% (715/723, 100%, and 1%, respectively. Of 190 patients for whom FNAC was performed for axilla, 170 had proven to have axillary lymph node metastases, and the rest had reactive hyperplasia or inflammatory cells. Conclusions. FNAC is rapid, accurate, outpatient based, and less complicated procedure and helps in diagnosis of breast cancer, benign diseases, and axillary involvement in experienced hands with less chance of false results.

Optimum Design and Operation of Cyclic Storage Systems; Lumped Approach

Directory of Open Access Journals (Sweden)

Leila Ostadrahimi

2007-01-01

Full Text Available Conjunctive use of surface and groundwater resources is a preferred approach in water resources management. Compared to dam construction, groundwater has certain advantages, among which are less costs, less sedimentation and evaporation, fewer water quality problems, and less social and cultural problems. To reduce the major problems associated with the development of large-scale surface impoundment systems, cyclic storage systems can be used as an alternative. A cyclic storage system (CYCS is an integrated interactive system consisting of two subsystems of surface water storage (reservoir and groundwater; this system together with artificial recharge is able to satisfy the predefined demands with rather high reliability. In order to optimize these systems, one must consider the hydraulic interactions between all the components, but unfortunately it has been neglected in many studies. In this article, a nonlinear optimization model for design and operation of cyclic storage systems has been developed using the lumped approach. In order to evaluate the model, its results have been compared with the results of a model in which distributed approach had been deployed, and so the efficiency of lumped models to solve the problems of cyclic storage systems has been investigated.

Breast Lumps: A 21‑Year Single‑Center Clinical and Histological ...

African Journals Online (AJOL)

Results: Only 38% of the patients came within 3 months of finding lumps in their breast. Onehundred and thirty‑seven patients (83%) had benign disease, i.e., fibroadenoma, mammary dysplasia, cysts, adenomas, tuberculosis, phyllodes tumor, mastitis, and lipoma. Only 16.9% i.e., 28 patients had breast cancer, out of which ...

A weighted least-squares lump correction algorithm for transmission-corrected gamma-ray nondestructive assay

International Nuclear Information System (INIS)

Prettyman, T.H.; Sprinkle, J.K. Jr.; Sheppard, G.A.

1993-01-01

With transmission-corrected gamma-ray nondestructive assay instruments such as the Segmented Gamma Scanner (SGS) and the Tomographic Gamma Scanner (TGS) that is currently under development at Los Alamos National Laboratory, the amount of gamma-ray emitting material can be underestimated for samples in which the emitting material consists of particles or lumps of highly attenuating material. This problem is encountered in the assay of uranium and plutonium-bearing samples. To correct for this source of bias, we have developed a least-squares algorithm that uses transmission-corrected assay results for several emitted energies and a weighting function to account for statistical uncertainties in the assay results. The variation of effective lump size in the fitted model is parameterized; this allows the correction to be performed for a wide range of lump-size distributions. It may be possible to use the reduced chi-squared value obtained in the fit to identify samples in which assay assumptions have been violated. We found that the algorithm significantly reduced bias in simulated assays and improved SGS assay results for plutonium-bearing samples. Further testing will be conducted with the TGS, which is expected to be less susceptible than the SGS to systematic source of bias

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

Science.gov (United States)

Peng, Youyi; Keenan, Susan M; Zhang, Qiang; Kholodovych, Vladyslav; Welsh, William J

2005-03-10

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the

Novel dimer based descriptors with solvational computation for QSAR study of oxadiazoylbenzoyl-ureas as novel insect-growth regulators.

Science.gov (United States)

Fan, Feng; Cheng, Jiagao; Li, Zhong; Xu, Xiaoyong; Qian, Xuhong

2010-02-01

Molecular aggregation state of bioactive compounds plays a key role in its bio-interactive procedure. In this article, based on the structure information of dimers, the simplest model of molecular aggregation state, and combined with solvational computation, total four descriptors (DeltaV, MR2, DeltaE(1), and DeltaE(2)) were calculated for QSAR study of a novel insect-growth regulator, N-(5-phenyl-1,3,4-oxadiazol-2-yl)-N'-benzoyl urea. Two QSAR models were constructed with r(2) = 0.671, q(2) = 0.516 and r(2) = 0.816, q(2) = 0.695, respectively. It implicates that the bioactivity may strongly depend on the characters of molecular aggregation state, especially on the dimeric transport ability from oil phase to water phase. Copyright 2009 Wiley Periodicals, Inc.

Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

Science.gov (United States)

Mager, P P; Rothe, H

1990-10-01

Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.

First molecular modeling report on novel arylpyrimidine kynurenine monooxygenase inhibitors through multi-QSAR analysis against Huntington's disease: A proposal to chemists!

Science.gov (United States)

Amin, Sk Abdul; Adhikari, Nilanjan; Jha, Tarun; Gayen, Shovanlal

2016-12-01

Huntington's disease (HD) is caused by mutation of huntingtin protein (mHtt) leading to neuronal cell death. The mHtt induced toxicity can be rescued by inhibiting the kynurenine monooxygenase (KMO) enzyme. Therefore, KMO is a promising drug target to address the neurodegenerative disorders such as Huntington's diseases. Fiftysix arylpyrimidine KMO inhibitors are structurally explored through regression and classification based multi-QSAR modeling, pharmacophore mapping and molecular docking approaches. Moreover, ten new compounds are proposed and validated through the modeling that may be effective in accelerating Huntington's disease drug discovery efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.

T-scale as a novel vector of topological descriptors for amino acids and its application in QSARs of peptides

Science.gov (United States)

Tian, Feifei; Zhou, Peng; Li, Zhiliang

2007-03-01

In this paper, a new topological descriptor T-scale is derived from principal component analysis (PCA) on the collected 67 kinds of structural and topological variables of 135 amino acids. Applying T-scale to three peptide panels as 58 angiotensin-converting enzyme (ACE) inhibitors, 20 thromboplastin inhibitors (TI) and 28 bovine lactoferricin-(17-31)-pentadecapeptides (LFB), the resulting QSAR models, constructed by partial least squares (PLS), are all superior to reference reports, with correlative coefficient r2 and cross-validated q2 of 0.845, 0.786; 0.996, 0.782 (0.988, 0.961); 0.760, 0.627, respectively.

Designing of phenol-based β-carbonic anhydrase1 inhibitors through QSAR, molecular docking, and MD simulation approach.

Science.gov (United States)

Ahamad, Shahzaib; Hassan, Md Imtaiyaz; Dwivedi, Neeraja

2018-05-01

Tuberculosis (Tb) is an airborne infectious disease caused by Mycobacterium tuberculosis. Beta-carbonic anhydrase 1 ( β-CA1 ) has emerged as one of the potential targets for new antitubercular drug development. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulation approaches were performed on a series of natural and synthetic phenol-based β-CA1 inhibitors. The developed 3D-QSAR model ( r 2  = 0.94, q 2  = 0.86, and pred_r 2  = 0.74) indicated that the steric and electrostatic factors are important parameters to modulate the bioactivity of phenolic compounds. Based on this indication, we designed 72 new phenolic inhibitors, out of which two compounds (D25 and D50) effectively stabilized β-CA1 receptor and, thus, are potential candidates for new generation antitubercular drug discovery program.

Pyrid-2-yl and 2-CyanoPhenyl fused heterocyclic compounds as human P2X3 inhibitors: a combined approach based on homology modelling, docking and QSAR analysis.

Science.gov (United States)

Janardhan, Sridhara; Seth, Subhendu; Viswanadhan, Vellarkad N

2014-02-01

P2X receptors are hetero-oligomeric proteins that function as membrane ion channels and are gated by extracellular ATP. The hP2X[Formula: see text] subunit is a constituent of the channels on a subset of sensory neurons involved in pain signaling, where ATP released by damaged and inflamed tissue can initiate action potentials. Hence, the inhibition of ATP-activated P2X3 receptor is an exciting approach for the treatment of inflammatory and neuropathic pain. Recently, the crystal structures of zebrafish P2X4 (zP2X4) were obtained in closed, apo state (PDB ID: 3I5D) and ATP-bound, open state (PDB ID: 4DW1). These structures were used to develop a homology model of human P2X3 (hP2X3 in order to identify through docking studies, the binding modes of known P2X3 inhibitors and their key active site interactions, along with a pharmacophore-based 3D-QSAR model for a series of 136 Pyrid-2-yl and 2-CyanoPhenyl fused heterocyclic compounds. These 3D-QSAR models have been developed with different combinations of training and test set divisions obtained by random separation, Jarvis-Patrick clustering, K-means clustering and sphere exclusion methods. The best predictive 3D-QSAR model resulted in training set R2 of 0.75, internal test set Q2 of 0.74, Pearson-R value of 0.87 and root mean square error of 0.37. The information generated by the pharmacophore model and docking analyses using the homology model provides valuable clues to design novel potent hP2X3 inhibitors.

A combined pharmacophore modeling, 3D-QSAR and molecular docking study of substituted bicyclo-[3.3.0]oct-2-enes as liver receptor homolog-1 (LRH-1) agonists

Science.gov (United States)

Lalit, Manisha; Gangwal, Rahul P.; Dhoke, Gaurao V.; Damre, Mangesh V.; Khandelwal, Kanchan; Sangamwar, Abhay T.

2013-10-01

A combined pharmacophore modelling, 3D-QSAR and molecular docking approach was employed to reveal structural and chemical features essential for the development of small molecules as LRH-1 agonists. The best HypoGen pharmacophore hypothesis (Hypo1) consists of one hydrogen-bond donor (HBD), two general hydrophobic (H), one hydrophobic aromatic (HYAr) and one hydrophobic aliphatic (HYA) feature. It has exhibited high correlation coefficient of 0.927, cost difference of 85.178 bit and low RMS value of 1.411. This pharmacophore hypothesis was cross-validated using test set, decoy set and Cat-Scramble methodology. Subsequently, validated pharmacophore hypothesis was used in the screening of small chemical databases. Further, 3D-QSAR models were developed based on the alignment obtained using substructure alignment. The best CoMFA and CoMSIA model has exhibited excellent rncv2 values of 0.991 and 0.987, and rcv2 values of 0.767 and 0.703, respectively. CoMFA predicted rpred2 of 0.87 and CoMSIA predicted rpred2 of 0.78 showed that the predicted values were in good agreement with the experimental values. Molecular docking analysis reveals that π-π interaction with His390 and hydrogen bond interaction with His390/Arg393 is essential for LRH-1 agonistic activity. The results from pharmacophore modelling, 3D-QSAR and molecular docking are complementary to each other and could serve as a powerful tool for the discovery of potent small molecules as LRH-1 agonists.

Effects of non-LTE multiplet dynamics on lumped-state modelling in moderate to high atomic number plasmas

International Nuclear Information System (INIS)

Whitney, K G; Dasgupta, A; Davis, J; Coverdale, C A

2007-01-01

Two atomic models of the population dynamics of substates within the n 4 and n = 3 multiplets of nickel-like tungsten and beryllium-like iron, respectively, are described in this paper. The flexible atomic code (FAC) is used to calculate the collisional and radiative couplings and energy levels of the excited states within these ionization stages. These atomic models are then placed within larger principal-quantum-number-based ionization dynamic models of both tungsten and iron plasmas. Collisional-radiative equilibrium calculations are then carried out using these models that demonstrate how the multiplet substates depart from local thermodynamic equilibrium (LTE) as a function of ion density. The effect of these deviations from LTE on the radiative and collisional deexcitation rates of lumped 3s, 3p, 3d, 4s, 4p, 4d and 4f states is then calculated and least-squares fits to the density dependence of these lumped-state rate coefficients are obtained. The calculations show that, with the use of lumped-state models (which are in common use), one can accurately model the L- and M-shell ionization dynamics occurring in present-day Z-pinch experiments only through the addition of these extra, non-LTE-induced, rate coefficient density dependences. However, the derivation and use of low-order polynomial fits to these density dependences makes lumped-state modelling both viable and of value for post-processing analyses

Painless lump over the forehead which turned painful: an unusual presentation of hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

S P Susheela

2015-05-01

Full Text Available Hepatocellular carcinoma (HCC is one of the most common malignancies and is known to most often present with symptomatology pertaining to local hepatic disease. Although HCC is known to metastasize to lungs, abdominal lymph nodes, adrenal glands and the vertebral column, it is rather rare to come across patients with skull metastasis. The manifestation of a solitary frontal bone metastasis leading to a painless lump over the forehead as the initial presenting feature of HCC is highly unusual. This case report pertains to a 40-year-old male patient who had initially observed a painless lump over his forehead that was gradually increasing in size over a span of 3 months. He sought medical attention when, after several months, the "painless lump" suddenly became painful. Investigations revealed the involvement of both the outer and the inner table of the frontal bone, and a biopsy revealed the histopathology to be that of HCC. On further investigation, he was found to have systemic disseminated disease involving both the left and right lungs and vertebrae and treatment was initiated with sorafenib. Despite an initial partial response, the patient subsequently succumbed to hepatic failure. This case report illustrates the fact that HCC can silently progress, and even lead to dissemination and distant metastases before becoming clinically evident.

Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models

International Nuclear Information System (INIS)

Esposito, Emilio Xavier; Hopfinger, Anton J.; Shao, Chi-Yu; Su, Bo-Han; Chen, Sing-Zuo; Tseng, Yufeng Jane

2015-01-01

Carbon nanotubes have become widely used in a variety of applications including biosensors and drug carriers. Therefore, the issue of carbon nanotube toxicity is increasingly an area of focus and concern. While previous studies have focused on the gross mechanisms of action relating to nanomaterials interacting with biological entities, this study proposes detailed mechanisms of action, relating to nanotoxicity, for a series of decorated (functionalized) carbon nanotube complexes based on previously reported QSAR models. Possible mechanisms of nanotoxicity for six endpoints (bovine serum albumin, carbonic anhydrase, chymotrypsin, hemoglobin along with cell viability and nitrogen oxide production) have been extracted from the corresponding optimized QSAR models. The molecular features relevant to each of the endpoint respective mechanism of action for the decorated nanotubes are also discussed. Based on the molecular information contained within the optimal QSAR models for each nanotoxicity endpoint, either the decorator attached to the nanotube is directly responsible for the expression of a particular activity, irrespective of the decorator's 3D-geometry and independent of the nanotube, or those decorators having structures that place the functional groups of the decorators as far as possible from the nanotube surface most strongly influence the biological activity. These molecular descriptors are further used to hypothesize specific interactions involved in the expression of each of the six biological endpoints. - Highlights: • Proposed toxicity mechanism of action for decorated nanotubes complexes • Discussion of the key molecular features for each endpoint's mechanism of action • Unique mechanisms of action for each of the six biological systems • Hypothesized mechanisms of action based on QSAR/QNAR predictive models

Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models

Energy Technology Data Exchange (ETDEWEB)

Esposito, Emilio Xavier, E-mail: emilio@exeResearch.com [exeResearch, LLC, 32 University Drive, East Lansing, MI 48823 (United States); The Chem21 Group, Inc., 1780 Wilson Drive, Lake Forest, IL 60045 (United States); Hopfinger, Anton J., E-mail: hopfingr@gmail.com [The Chem21 Group, Inc., 1780 Wilson Drive, Lake Forest, IL 60045 (United States); College of Pharmacy MSC09 5360, 1 University of New Mexico, Albuquerque, NM, 87131 (United States); Shao, Chi-Yu [Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 106, Taiwan (China); Su, Bo-Han [Department of Computer Science and Information Engineering, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 106, Taiwan (China); Chen, Sing-Zuo [Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 106, Taiwan (China); Tseng, Yufeng Jane, E-mail: yjtseng@csie.ntu.edu.tw [Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1 Sec. 4, Roosevelt Road, Taipei 106, Taiwan (China)

2015-10-01

Carbon nanotubes have become widely used in a variety of applications including biosensors and drug carriers. Therefore, the issue of carbon nanotube toxicity is increasingly an area of focus and concern. While previous studies have focused on the gross mechanisms of action relating to nanomaterials interacting with biological entities, this study proposes detailed mechanisms of action, relating to nanotoxicity, for a series of decorated (functionalized) carbon nanotube complexes based on previously reported QSAR models. Possible mechanisms of nanotoxicity for six endpoints (bovine serum albumin, carbonic anhydrase, chymotrypsin, hemoglobin along with cell viability and nitrogen oxide production) have been extracted from the corresponding optimized QSAR models. The molecular features relevant to each of the endpoint respective mechanism of action for the decorated nanotubes are also discussed. Based on the molecular information contained within the optimal QSAR models for each nanotoxicity endpoint, either the decorator attached to the nanotube is directly responsible for the expression of a particular activity, irrespective of the decorator's 3D-geometry and independent of the nanotube, or those decorators having structures that place the functional groups of the decorators as far as possible from the nanotube surface most strongly influence the biological activity. These molecular descriptors are further used to hypothesize specific interactions involved in the expression of each of the six biological endpoints. - Highlights: • Proposed toxicity mechanism of action for decorated nanotubes complexes • Discussion of the key molecular features for each endpoint's mechanism of action • Unique mechanisms of action for each of the six biological systems • Hypothesized mechanisms of action based on QSAR/QNAR predictive models.

GEYSER/TONUS: A coupled multi-D lumped parameter code for reactor thermal hydraulics analysis in case of severe accidents

Energy Technology Data Exchange (ETDEWEB)

Petit, M.; Durin, M.; Gauvain, J. [Commissariat a l`Energie Atomique, Gif sur Yvette (France)

1995-09-01

In many countries, the safety requirements for future light water reactors include accounting for severe accidents in the design process. As far as the containment is concerned, the design must now include mitigation features to limit the pressure and temperature inside the building. Hydrogen concentration is also a major issue for severe accidents. In this context, new needs appear for the modeling of the thermal hydraulics inside the containment. It requires the description of complex phenomena such as condensation, stratification, transport of gases and aerosols, heat transfers. Moreover, the effect of mitigation systems will increase the heterogeneities in the building, and most of those phenomena can be coupled, as for example hydrogen stratification and condensation. To model such a complex situation, the use of multi-dimensional computer codes seems to be necessary in case of large volumes. The aim of the GEYSER/TONUS computer code is to fulfill this need. This code is currently under development at CEA in Saclay. It will allow the coupling of parts of the containment described in a lumped parameter manner, together with meshed parts. Emphasis is put on the numerical methods used to solve the transient problem, as the objective is to be able to treat complete scenarios. Physical models of classical lumped parameters codes will adapted for the spatially described zones. The code is developed in the environment of the CASTEM 2000/TRIO EF system which allows, thanks to its modular conception, to construct sophisticated applications based upon it.

Reservoir theory, groundwater transit time distributions, and lumped parameter models

International Nuclear Information System (INIS)

Etcheverry, D.; Perrochet, P.

1999-01-01

The relation between groundwater residence times and transit times is given by the reservoir theory. It allows to calculate theoretical transit time distributions in a deterministic way, analytically, or on numerical models. Two analytical solutions validates the piston flow and the exponential model for simple conceptual flow systems. A numerical solution of a hypothetical regional groundwater flow shows that lumped parameter models could be applied in some cases to large-scale, heterogeneous aquifers. (author)

Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

Science.gov (United States)

Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E

2013-12-01

Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.

Estimation of time to rupture in a fire using 6FIRE, a lumped parameter UF6 cylinder transient heat transfer/stress analysis model

International Nuclear Information System (INIS)

Williams, W.R.; Anderson, J.C.

1995-01-01

The transportation of UF 6 is subject to regulations requiring the evaluation of packaging under a sequence of hypothetical accident conditions including exposure to a 30-min 800 degree C (1475 degree F) fire [10 CFR 71.73(c)(3)]. An issue of continuing interest is whether bare cylinders can withstand such a fire without rupturing. To address this issue, a lumped parameter heat transfer/stress analysis model (6FIRE) has been developed to simulate heating to the point of rupture of a cylinder containing UF 6 when it is exposed to a fire. The model is described, then estimates of time to rupture are presented for various cylinder types, fire temperatures, and fill conditions. An assessment of the quantity of UF 6 released from containment after rupture is also presented. Further documentation of the model is referenced

The lumped heat capacity method applied to target heating

OpenAIRE

Rickards, J.

2013-01-01

The temperature of metal samples was measured while they were bombarded by the beam from the a particle accelerator. The evolution of the temperature with time can be explained using the lumped heat capacity method of heat transfer. A strong dependence on the type of mounting was found. Se midió la temperatura de muestras metálicas al ser bombardeadas por el haz de iones del Acelerador Pelletron del Instituto de Física. La evolución de la temperatura con el tiempo se puede explicar usando ...

Probing lumps of wee partons in deep inelastic scattering

International Nuclear Information System (INIS)

Buchmueller, W.

1994-06-01

Recently, the ZEUS collaboration has reported on several remarkable properties of events with a large rapidity gap in deep inelastic scattering. We suggest that the mechanism underlying these events is the scattering of electrons off lumps of wee partons inside the proton. Based on an effective lagrangian approach the Q 2 -, x- and W-distributions are evaluated. For sufficiently small invariant mass of the detected hadronic system, the mechanism implies leading twist behaviour. The x- and W-distributions are determined by the Lipatov exponent which governs the behaviour of parton densities at small x. (orig.)

Lumped-parameter fuel rod model for rapid thermal transients

International Nuclear Information System (INIS)

Perkins, K.R.; Ramshaw, J.D.

1975-07-01

The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company

Exploring 2D and 3D QSARs of benzimidazole derivatives as transient receptor potential melastatin 8 (TRPM8 antagonists using MLR and kNN-MFA methodology

Directory of Open Access Journals (Sweden)

Kamlendra Singh Bhadoriya

2016-09-01

Full Text Available TRPM8 is now best known as a cold- and menthol-activated channel implicated in thermosensation. TRPM8 is specifically expressed in a subset of pain- and temperature-sensing neuron. TRPM8 plays a major role in the sensation of cold and cooling substances. TRPM8 is a potential new target for the treatment of painful conditions. Thus, TRPM8 antagonists represent a new, novel and potentially useful treatment strategy to treat various disease states such as urological disorders, asthma, COPD, prostate and colon cancers, and painful conditions related to cold, such as cold allodynia and cold hyperalgesia. Better tools such as potent and specific TRPM8 antagonists are mandatory as high unmet medical need for such progress. To achieve this objective quantitative structure–activity relationship (QSAR studies were carried out on a series of 25 benzimidazole-containing TRPM8 antagonists to investigate the structural requirements of their inhibitory activity against cTRPM8. The statistically significant best 2D-QSAR model having correlation coefficient r2 = 0.88 and cross-validated squared correlation coefficient q2 = 0.64 with external predictive ability of pred_r2 = 0.69 was developed by SW-MLR. The physico-chemical descriptors such as polarizabilityAHP, kappa2, XcompDipole, +vePotentialSurfaceArea, XKMostHydrophilic were found to show a significant correlation with biological activity in benzimidazole derivatives. Molecular field analysis was used to construct the best 3D-QSAR model using SW-kNN method, showing good correlative and predictive capabilities in terms of q2 = 0.81 and pred_r2 = 0.55. Developed kNN-MFA model highlighted the importance of shape of the molecules, i.e., steric & electrostatic descriptors at the grid points S_774 & E_1024 for TRPM8 receptor binding. These models (2D & 3D were found to yield reliable clues for further optimization of benzimidazole derivatives in the data set. The information rendered by 2D- and 3D-QSAR

First report on 3D-QSAR and molecular dynamics based docking studies of GCPII inhibitors for targeted drug delivery applications

Science.gov (United States)

Pandit, Amit; Sengupta, Sagnik; Krishnan, Mena Asha; Reddy, Ramesh B.; Sharma, Rajesh; Venkatesh, Chelvam

2018-05-01

Prostate Specific Membrane Antigen (PSMA) or Glutamate carboxypeptidase II (GCPII) has been identified as an important target in diagnosis and therapy of prostate cancer. Among several types of inhibitors, urea based inhibitors are the most common and widely employed in preclinical and clinical studies. Computational studies have been carried out to uncover active sites and interaction of PSMA inhibitors with the protein by modifying the core structure of the ligand. Analysis of the literature, however, show lack of 3-D quantitative structure activity relationship (QSAR) and molecular dynamics based molecular docking study to identify structural modifications responsible for better GCPII inhibitory activity. The present study aims to fulfil this gap by analysing well known PSMA inhibitors reported in the literature with known experimental PSMA inhibition constants. Also in order to validate the in silico study, a new GCPII inhibitor 7 was designed, synthesized and experimental PSMA enzyme inhibition was evaluated by using freshly isolated PSMA protein from human cancer cell line derived from lymph node, LNCaP. 3D-QSAR CoMFA models on 58 urea based GCPII inhibitors were generated, and the best correlation was obtained in Gast-Huck charge assigning method with q2, r2 and predictive r2 values as 0.592, 0.995 and 0.842 respectively. Moreover, steric, electrostatic, and hydrogen bond donor field contribution analysis provided best statistical values from CoMSIA model (q2, r2 and predictive r2 as 0.527, 0.981 and 0.713 respectively). Contour maps study revealed that electrostatic field contribution is the major factor for discovering better binding affinity ligands. Further molecular dynamic assisted molecular docking was also performed on GCPII receptor (PDB ID 4NGM) and most active GCPII inhibitor, DCIBzL. 4NGM co-crystallised ligand, JB7 was used to validate the docking procedure and the amino acid interactions present in JB7 are compared with DCIBzL. The results

New equivalent lumped electrical circuit for piezoelectric transformers.

Science.gov (United States)

Gonnard, Paul; Schmitt, P M; Brissaud, Michel

2006-04-01

A new equivalent circuit is proposed for a contour-vibration-mode piezoelectric transformer (PT). It is shown that the usual lumped equivalent circuit derived from the conventional Mason approach is not accurate. The proposed circuit, built on experimental measurements, makes an explicit difference between the elastic energies stored respectively on the primary and secondary parts. The experimental and theoretical resonance frequencies with the secondary in open or short circuit are in good agreement as well as the output "voltage-current" characteristic and the optimum efficiency working point. This circuit can be extended to various PT configurations and appears to be a useful tool for modeling electronic devices that integrate piezoelectric transformers.

Lumped versus distributed thermoregulatory control: results from a three-dimensional dynamic model.

Science.gov (United States)

Werner, J; Buse, M; Foegen, A

1989-01-01

In this study we use a three-dimensional model of the human thermal system, the spatial grid of which is 0.5 ... 1.0 cm. The model is based on well-known physical heat-transfer equations, and all parameters of the passive system have definite physical values. According to the number of substantially different areas and organs, 54 spatially different values are attributed to each physical parameter. Compatibility of simulation and experiment was achieved solely on the basis of physical considerations and physiological basic data. The equations were solved using a modification of the alternating direction implicit method. On the basis of this complex description of the passive system close to reality, various lumped and distributed parameter control equations were tested for control of metabolic heat production, blood flow and sweat production. The simplest control equations delivering results on closed-loop control compatible with experimental evidence were determined. It was concluded that it is essential to take into account the spatial distribution of heat production, blood flow and sweat production, and that at least for control of shivering, distributed controller gains different from the pattern of distribution of muscle tissue are required. For sweat production this is not so obvious, so that for simulation of sweating control after homogeneous heat load a lumped parameter control may be justified. Based on these conclusions three-dimensional temperature profiles for cold and heat load and the dynamics for changes of the environmental conditions were computed. In view of the exact simulation of the passive system and the compatibility with experimentally attainable variables there is good evidence that those values extrapolated by the simulation are adequately determined. The model may be used both for further analysis of the real thermoregulatory mechanisms and for special applications in environmental and clinical health care.

Acute lymphoblastic leukemia presenting as a breast lump: A report of two cases

Directory of Open Access Journals (Sweden)

Syed Besina

2013-01-01

Full Text Available Extra-medullary leukemic infiltration of the breast by acute lymphoblastic leukemia (ALL is very rare. We report two cases of ALL presenting as breast masses and diagnosed on fine-needle aspiration (FNA. Our first patient, a post-partum 30-year-old female, developed bilateral breast lumps in her last trimester of pregnancy and complained of easy fatigability. Our second patient, a 14-year-old girl, presented with a right-breast lump of 1-week duration. She had received treatment for ALL 1 year back and had been in complete remission for the last 1 year. FNA of the breast nodules done in both the cases revealed diffuse infiltration by lymphoblasts. Subsequent hematological investigations confirmed bone marrow involvement by ALL in the first case and extra-medullary relapse in the second case. Fine-needle aspiration cytology (FNAC is an easy and cost effective method for the early diagnosis of metastatic leukemic infiltration, avoiding unnecessary excisional biopsies in such cases.

Some error estimates for the lumped mass finite element method for a parabolic problem

KAUST Repository

Chatzipantelidis, P.; Lazarov, R. D.; Thomé e, V.

2012-01-01

for the standard Galerkin method carry over to the lumped mass method whereas nonsmooth initial data estimates require special assumptions on the triangulation. We also discuss the application to time discretization by the backward Euler and Crank-Nicolson methods

Synthesis, QSAR, and Molecular Dynamics Simulation of Amidino-substituted Benzimidazoles as Dipeptidyl Peptidase III Inhibitors.

Science.gov (United States)

Rastija, Vesna; Agić, Dejan; Tomiš, Sanja; Nikolič, Sonja; Hranjec, Marijana; Grace, Karminski-Zamola; Abramić, Marija

2015-01-01

A molecular modeling study is performed on series of benzimidazol-based inhibitors of human dipeptidyl peptidase III (DPP III). An eight novel compounds were synthesized in excellent yields using green chemistry approach. This study is aimed to elucidate the structural features of benzimidazole derivatives required for antagonism of human DPP III activity using Quantitative Structure-Activity Relationship (QSAR) analysis, and to understand the mechanism of one of the most potent inhibitor binding into the active site of this enzyme, by molecular dynamics (MD) simulations. The best model obtained includes S3K and RDF045m descriptors which have explained 89.4 % of inhibitory activity. Depicted moiety for strong inhibition activity matches to the structure of most potent compound. MD simulation has revealed importance of imidazolinyl and phenyl groups in the mechanism of binding into the active site of human DPP III.

Integration of QSAR models for bioconcentration suitable for REACH

Energy Technology Data Exchange (ETDEWEB)

Gissi, Andrea [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy); Dipartimento di Farmacia — Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, via Orabona 4, I-70125 Bari (Italy); Nicolotti, Orazio; Carotti, Angelo; Gadaleta, Domenico [Dipartimento di Farmacia — Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, via Orabona 4, I-70125 Bari (Italy); Lombardo, Anna [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy); Benfenati, Emilio, E-mail: benfenati@marionegri.it [Laboratory of Chemistry and Environmental Toxicology, IRCCS - Istituto di Ricerche Farmacologiche “Mario Negri”, via Giuseppe La Masa 19, 20156 Milan (Italy)

2013-07-01

QSAR (Quantitative Structure Activity Relationship) models can be a valuable alternative method to replace or reduce animal test required by REACH. In particular, some endpoints such as bioconcentration factor (BCF) are easier to predict and many useful models have been already developed. In this paper we describe how to integrate two popular BCF models to obtain more reliable predictions. In particular, the herein presented integrated model relies on the predictions of two among the most used BCF models (CAESAR and Meylan), together with the Applicability Domain Index (ADI) provided by the software VEGA. Using a set of simple rules, the integrated model selects the most reliable and conservative predictions and discards possible outliers. In this way, for the prediction of the 851 compounds included in the ANTARES BCF dataset, the integrated model discloses a R{sup 2} (coefficient of determination) of 0.80, a RMSE (Root Mean Square Error) of 0.61 log units and a sensitivity of 76%, with a considerable improvement in respect to the CAESAR (R{sup 2} = 0.63; RMSE = 0.84 log units; sensitivity 55%) and Meylan (R{sup 2} = 0.66; RMSE = 0.77 log units; sensitivity 65%) without discarding too many predictions (118 out of 851). Importantly, considering solely the compounds within the new integrated ADI, the R{sup 2} increased to 0.92, and the sensitivity to 85%, with a RMSE of 0.44 log units. Finally, the use of properly set safety thresholds applied for monitoring the so called “suspicious” compounds, which are those chemicals predicted in proximity of the border normally accepted to discern non-bioaccumulative from bioaccumulative substances, permitted to obtain an integrated model with sensitivity equal to 100%. - Highlights: • Applying two independent QSAR models for bioconcentration factor increases the prediction. • The concordance of the models is an important component of the integration. • The measurement of the applicability domain improves the

Integration of QSAR models for bioconcentration suitable for REACH

International Nuclear Information System (INIS)

Gissi, Andrea; Nicolotti, Orazio; Carotti, Angelo; Gadaleta, Domenico; Lombardo, Anna; Benfenati, Emilio

2013-01-01

QSAR (Quantitative Structure Activity Relationship) models can be a valuable alternative method to replace or reduce animal test required by REACH. In particular, some endpoints such as bioconcentration factor (BCF) are easier to predict and many useful models have been already developed. In this paper we describe how to integrate two popular BCF models to obtain more reliable predictions. In particular, the herein presented integrated model relies on the predictions of two among the most used BCF models (CAESAR and Meylan), together with the Applicability Domain Index (ADI) provided by the software VEGA. Using a set of simple rules, the integrated model selects the most reliable and conservative predictions and discards possible outliers. In this way, for the prediction of the 851 compounds included in the ANTARES BCF dataset, the integrated model discloses a R 2 (coefficient of determination) of 0.80, a RMSE (Root Mean Square Error) of 0.61 log units and a sensitivity of 76%, with a considerable improvement in respect to the CAESAR (R 2 = 0.63; RMSE = 0.84 log units; sensitivity 55%) and Meylan (R 2 = 0.66; RMSE = 0.77 log units; sensitivity 65%) without discarding too many predictions (118 out of 851). Importantly, considering solely the compounds within the new integrated ADI, the R 2 increased to 0.92, and the sensitivity to 85%, with a RMSE of 0.44 log units. Finally, the use of properly set safety thresholds applied for monitoring the so called “suspicious” compounds, which are those chemicals predicted in proximity of the border normally accepted to discern non-bioaccumulative from bioaccumulative substances, permitted to obtain an integrated model with sensitivity equal to 100%. - Highlights: • Applying two independent QSAR models for bioconcentration factor increases the prediction. • The concordance of the models is an important component of the integration. • The measurement of the applicability domain improves the prediction. • The use of a

QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification

KAUST Repository

Sudhakaran, Sairam

2013-03-01

Ozonation is an oxidation process for the removal of organic micropollutants (OMPs) from water and the chemical reaction is governed by second-order kinetics. An advanced oxidation process (AOP), wherein the hydroxyl radicals (OH radicals) are generated, is more effective in removing a wider range of OMPs from water than direct ozonation. Second-order rate constants (kOH and kO3) are good indices to estimate the oxidation efficiency, where higher rate constants indicate more rapid oxidation. In this study, quantitative structure activity relationships (QSAR) models for O3 and AOP processes were developed, and rate constants, kOH and kO3, were predicted based on target compound properties. The kO3 and kOH values ranged from 5 * 10-4 to 105 M-1s-1 and 0.04 to 18 * (109) M-1 s-1, respectively. Several molecular descriptors which potentially influence O3 and OH radical oxidation were identified and studied. The QSAR-defining descriptors were double bond equivalence (DBE), ionisation potential (IP), electron-affinity (EA) and weakly-polar component of solvent accessible surface area (WPSA), and the chemical and statistical significance of these descriptors was discussed. Multiple linear regression was used to build the QSAR models, resulting in high goodness-of-fit, r2 (>0.75). The models were validated by internal and external validation along with residual plots. © 2012 Elsevier Ltd.

Deciphering the Structural Requirements of Nucleoside Bisubstrate Analogues for Inhibition of MbtA in Mycobacterium tuberculosis: A FB-QSAR Study and Combinatorial Library Generation for Identifying Potential Hits.

Science.gov (United States)

Maganti, Lakshmi; Das, Sanjit Kumar; Mascarenhas, Nahren Manuel; Ghoshal, Nanda

2011-10-01

The re-emergence of tuberculosis infections, which are resistant to conventional drug therapy, has steadily risen in the last decade. Inhibitors of aryl acid adenylating enzyme known as MbtA, involved in siderophore biosynthesis in Mycobacterium tuberculosis, are being explored as potential antitubercular agents. The ability to identify fragments that interact with a biological target is a key step in fragment based drug design (FBDD). To expand the boundaries of quantitative structure activity relationship (QSAR) paradigm, we have proposed a Fragment Based QSAR methodology, referred here in as FB-QSAR, for deciphering the structural requirements of a series of nucleoside bisubstrate analogs for inhibition of MbtA, a key enzyme involved in siderophore biosynthetic pathway. For the development of FB-QSAR models, statistical techniques such as stepwise multiple linear regression (SMLR), genetic function approximation (GFA) and GFAspline were used. The predictive ability of the generated models was validated using different statistical metrics, and similarity-based coverage estimation was carried out to define applicability boundaries. To aid the creation of novel antituberculosis compounds, a bioisosteric database was enumerated using the combichem approach endorsed mining in a lead-like chemical space. The generated library was screened using an integrated in-silico approach and potential hits identified. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

QSAR Methods to Screen Endocrine Disruptors

Directory of Open Access Journals (Sweden)

Nicola Porta

2016-08-01

Full Text Available The identification of endocrine disrupting chemicals (EDCs is one of the important goals of environmental chemical hazard screening. We report on in silico methods addressing toxicological studies about EDCs with a special focus on the application of QSAR models for screening purpose. Since Estrogen-like (ER activity has been extensively studied, the majority of the available models are based on ER-related endpoints. Some of these models are here reviewed and described. As example for their application, we screen an assembled dataset of candidate substitutes for some known EDCs belonging to the chemical classes of phthalates, bisphenols and parabens, selected considering their toxicological relevance and broad application, with the general aim of preliminary assessing their ED potential. The goal of the substitution processes is to advance inherently safer chemicals and products, consistent with the principles of green chemistry. Results suggest that the integration of a family of different models accounting for different endpoints can be a convenient way to describe ED as properly as possible and allow also both to increase the confidence of the predictions and to maximize the probability that most active compounds are correctly found.

Energy-state formulation of lumped volume dynamic equations with application to a simplified free piston Stirling engine

Science.gov (United States)

Daniele, C. J.; Lorenzo, C. F.

1979-01-01

Lumped volume dynamic equations are derived using an energy-state formulation. This technique requires that kinetic and potential energy state functions be written for the physical system being investigated. To account for losses in the system, a Rayleigh dissipation function is also formed. Using these functions, a Lagrangian is formed and using Lagrange's equation, the equations of motion for the system are derived. The results of the application of this technique to a lumped volume are used to derive a model for the free-piston Stirling engine. The model was simplified and programmed on an analog computer. Results are given comparing the model response with experimental data.

QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

Science.gov (United States)

Akbari, Somaye; Zebardast, Tannaz; Zarghi, Afshin; Hajimahdi, Zahra

2017-01-01

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R 2 ) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q 2 ) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.

A Size Reduction Technique for Mobile Phone PIFA Antennas Using Lumped Inductors

DEFF Research Database (Denmark)

Thaysen, Jesper; Jakobsen, Kaj Bjarne

2005-01-01

A size reduction technique for the planar inverted-F antenna (PIFA) is presented. An 18 nH lumped inductor is used in addition to a small 0.3 cm3 PIFA. The PIFA is located on dielectric foam, 5 mm above a 40 mm × 100 mm ground plane. It is possible to reduce the center frequency (|S11|min) by 33 ...

Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.

Science.gov (United States)

Chirico, Nicola; Gramatica, Paola

2011-09-26

The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.

2D QSAR studies of the inhibitory activity of a series of substituted purine derivatives against c-Src tyrosine kinase

Directory of Open Access Journals (Sweden)

Mukesh C. Sharma

2016-07-01

Full Text Available A series of 34 substituted purine analogues derivatives were subjected to quantitative structure-activity relationship analyses as inhibitors of c-Src tyrosine kinase. Partial least squares regression was applied to derive QSAR models, which were further validated for statistical significance by internal and external validation. The best QSAR model developed had a good predictive correlation coefficient (r2 of 0.8319, a significant cross-validated correlation coefficient (q2 of 0.7550, and an r2 for the external test set (pred_r2 of 0.7983. It was developed from the PLS method with descriptors including the SsCH3E-index, H-Donor Count, T_2_Cl_3, and negative correlation with SsOHcount. The current study provides better insight into the future design of more potent c-Src tyrosine kinase inhibitors prior to synthesis.

Development of a QSAR model for binding of tripeptides and tripeptidomimetics to the human intestinal di-/tripeptide transporter hPEPT1

DEFF Research Database (Denmark)

Andersen, Rikke; Jørgensen, Flemming Steen; Olsen, Lars

2006-01-01

The aim of this study was to develop a three-dimensional quantitative structure-activity relationship (QSAR) model for binding of tripeptides and tripeptidomimetics to hPEPT1 based on a series of 25 diverse tripeptides....

Generalized Kutta–Joukowski theorem for multi-vortex and multi-airfoil flow (a lumped vortex model

Directory of Open Access Journals (Sweden)

Bai Chenyuan

2014-02-01

Full Text Available For purpose of easy identification of the role of free vortices on the lift and drag and for purpose of fast or engineering evaluation of forces for each individual body, we will extend in this paper the Kutta–Joukowski (KJ theorem to the case of inviscid flow with multiple free vortices and multiple airfoils. The major simplification used in this paper is that each airfoil is represented by a lumped vortex, which may hold true when the distances between vortices and bodies are large enough. It is found that the Kutta–Joukowski theorem still holds provided that the local freestream velocity and the circulation of the bound vortex are modified by the induced velocity due to the outside vortices and airfoils. We will demonstrate how to use the present result to identify the role of vortices on the forces according to their position, strength and rotation direction. Moreover, we will apply the present results to a two-cylinder example of Crowdy and the Wagner example to demonstrate how to perform fast force approximation for multi-body and multi-vortex problems. The lumped vortex assumption has the advantage of giving such kinds of approximate results which are very easy to use. The lack of accuracy for such a fast evaluation will be compensated by a rigorous extension, with the lumped vortex assumption removed and with vortex production included, in a forthcoming paper.

Intense deuterium nuclear fusion of pycnodeuterium-lumps coagulated locally within highly deuterated atom clusters

CERN Document Server

Yoshiaki, A; Zhang, Y C

2002-01-01

Embedded nano-Pd particles of 5 nm in size instantly abundant D-atoms more than 250% in the atomic ratio against Pd-atoms at room temperature when they are kept in D sub 2 gas pressurized to less than 10 atm. In such ultrahigh densities, 2-4 D-atoms can be coagulated inside each octahedral space of Pd lattice (pycnodeuterium-lump). When a stimulation energy such as latticequake causing by ultrasonic wave was supplied to those highly deuterated Pd particles, intense deuterium nuclear fusion (''solid fusion'') was generated there and both excess heat and sup 4 He gas were abundantly produced. Naturally, these facts can not be realized at all in bulk Pd. The results show that the nuclear fusion occurs without any hazardous rays in pycnodeuterium-lumps coagulated locally inside the each cell of the host metal lattice. These unit cells correspond to minimum unit of the solid fusion reactor as a ''Lattice Reactor''. (author)

Application of Biologically-Based Lumping To Investigate the Toxicological Interactions of a Complex Gasoline Mixture

Science.gov (United States)

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. However, investigators have often considered complex mixtures as one lumped entity. Valuable information can be obtained from these exp...

Exploring possible mechanisms of action for the nanotoxicity and protein binding of decorated nanotubes: interpretation of physicochemical properties from optimal QSAR models.

Science.gov (United States)

Esposito, Emilio Xavier; Hopfinger, Anton J; Shao, Chi-Yu; Su, Bo-Han; Chen, Sing-Zuo; Tseng, Yufeng Jane

2015-10-01

Carbon nanotubes have become widely used in a variety of applications including biosensors and drug carriers. Therefore, the issue of carbon nanotube toxicity is increasingly an area of focus and concern. While previous studies have focused on the gross mechanisms of action relating to nanomaterials interacting with biological entities, this study proposes detailed mechanisms of action, relating to nanotoxicity, for a series of decorated (functionalized) carbon nanotube complexes based on previously reported QSAR models. Possible mechanisms of nanotoxicity for six endpoints (bovine serum albumin, carbonic anhydrase, chymotrypsin, hemoglobin along with cell viability and nitrogen oxide production) have been extracted from the corresponding optimized QSAR models. The molecular features relevant to each of the endpoint respective mechanism of action for the decorated nanotubes are also discussed. Based on the molecular information contained within the optimal QSAR models for each nanotoxicity endpoint, either the decorator attached to the nanotube is directly responsible for the expression of a particular activity, irrespective of the decorator's 3D-geometry and independent of the nanotube, or those decorators having structures that place the functional groups of the decorators as far as possible from the nanotube surface most strongly influence the biological activity. These molecular descriptors are further used to hypothesize specific interactions involved in the expression of each of the six biological endpoints. Copyright © 2015 Elsevier Inc. All rights reserved.

Prediction of drug-related cardiac adverse effects in humans--B: use of QSAR programs for early detection of drug-induced cardiac toxicities.

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Frid, Anna A; Matthews, Edwin J

2010-04-01

This report describes the use of three quantitative structure-activity relationship (QSAR) programs to predict drug-related cardiac adverse effects (AEs), BioEpisteme, MC4PC, and Leadscope Predictive Data Miner. QSAR models were constructed for 9 cardiac AE clusters affecting Purkinje nerve fibers (arrhythmia, bradycardia, conduction disorder, electrocardiogram, palpitations, QT prolongation, rate rhythm composite, tachycardia, and Torsades de pointes) and 5 clusters affecting the heart muscle (coronary artery disorders, heart failure, myocardial disorders, myocardial infarction, and valve disorders). The models were based on a database of post-marketing AEs linked to 1632 chemical structures, and identical training data sets were configured for three QSAR programs. Model performance was optimized and shown to be affected by the ratio of the number of active to inactive drugs. Results revealed that the three programs were complementary and predictive performances using any single positive, consensus two positives, or consensus three positives were as follows, respectively: 70.7%, 91.7%, and 98.0% specificity; 74.7%, 47.2%, and 21.0% sensitivity; and 138.2, 206.3, and 144.2 chi(2). In addition, a prospective study using AE data from the U.S. Food and Drug Administration's (FDA's) MedWatch Program showed 82.4% specificity and 94.3% sensitivity. Furthermore, an external validation study of 18 drugs with serious cardiotoxicity not considered in the models had 88.9% sensitivity. Published by Elsevier Inc.

QSAR, docking, dynamic simulation and quantum mechanics studies to explore the recognition properties of cholinesterase binding sites.

Science.gov (United States)

Correa-Basurto, J; Bello, M; Rosales-Hernández, M C; Hernández-Rodríguez, M; Nicolás-Vázquez, I; Rojo-Domínguez, A; Trujillo-Ferrara, J G; Miranda, René; Flores-Sandoval, C A

2014-02-25

A set of 84 known N-aryl-monosubstituted derivatives (42 amides: series 1 and 2, and 42 imides: series 3 an 4, from maleic and succinic anhydrides, respectively) that display inhibitory activity toward both acetylcholinesterase and butyrylcholinesterase (ChEs) was considered for Quantitative structure-activity relationship (QSAR) studies. These QSAR studies employed docking data from both ChEs that were previously submitted to molecular dynamics (MD) simulations. Donepezil and galanthamine stereoisomers were included to analyze their quantum mechanics properties and for validating the docking procedure. Quantum parameters such as frontier orbital energies, dipole moment, molecular volume, atomic charges, bond length and reactivity parameters were measured, as well as partition coefficients, molar refractivity and polarizability were also analyzed. In order to evaluate the obtained equations, four compounds: 1a (4-oxo-4-(phenylamino)butanoic acid), 2a ((2Z)-4-oxo-4-(phenylamino)but-2-enoic acid), 3a (2-phenylcyclopentane-1,3-dione) and 4a (2-phenylcyclopent-4-ene-1,3-dione) were employed as independent data set, using only equations with r(m(test))²>0.5. It was observed that residual values gave low value in almost all series, excepting in series 1 for compounds 3a and 4a, and in series 4 for compounds 1a, 2a and 3a, giving a low value for 4a. Consequently, equations seems to be specific according to the structure of the evaluated compound, that means, series 1 fits better for compound 1a, series 3 or 4 fits better for compounds 3a or 4a. Same behavior was observed in the butyrylcholinesterase (BChE). Therefore, obtained equations in this QSAR study could be employed to calculate the inhibition constant (Ki) value for compounds having a similar structure as N-aryl derivatives described here. The QSAR study showed that bond lengths, molecular electrostatic potential and frontier orbital energies are important in both ChE targets. Docking studies revealed that

Electron-correlation based externally predictive QSARs for mutagenicity of nitrated-PAHs in Salmonella typhimurium TA100.

Science.gov (United States)

Reenu; Vikas

2014-03-01

In quantitative modeling, there are two major aspects that decide reliability and real external predictivity of a structure-activity relationship (SAR) based on quantum chemical descriptors. First, the information encoded in employed molecular descriptors, computed through a quantum-mechanical method, should be precisely estimated. The accuracy of the quantum-mechanical method, however, is dependent upon the amount of electron-correlation it incorporates. Second, the real external predictivity of a developed quantitative SAR (QSAR) should be validated employing an external prediction set. In this work, to analyze the role of electron-correlation, QSAR models are developed for a set of 51 ubiquitous pollutants, namely, nitrated monocyclic and polycyclic aromatic hydrocarbons (nitrated-AHs and PAHs) having mutagenic activity in TA100 strain of Salmonella typhimurium. The quality of the models, through state-of-the-art external validation procedures employing an external prediction set, is compared to the best models known in the literature for mutagenicity. The molecular descriptors whose electron-correlation contribution is analyzed include total energy, energy of HOMO and LUMO, and commonly employed electron-density based descriptors such as chemical hardness, chemical softness, absolute electronegativity and electrophilicity index. The electron-correlation based QSARs are also compared with those developed using quantum-mechanical descriptors computed with advanced semi-empirical (SE) methods such as PM6, PM7, RM1, and ab initio methods, namely, the Hartree-Fock (HF) and the density functional theory (DFT). The models, developed using electron-correlation contribution of the quantum-mechanical descriptors, are found to be not only reliable but also satisfactorily predictive when compared to the existing robust models. The robustness of the models based on descriptors computed through advanced SE methods, is also observed to be comparable to those developed with

Lumped model for rotational modes in phononic crystals

KAUST Repository

Peng, Pai

2012-10-16

We present a lumped model for the rotational modes induced by the rotational motion of individual scatterers in two-dimensional phononic crystals comprised of square arrays of solid cylindrical scatterers in solid hosts. The model provides a physical interpretation of the origin of the rotational modes, reveals the important role played by the rotational motion in determining the band structure, and reproduces the dispersion relations in a certain range. The model increases the possibilities of manipulating wave propagation in phononic crystals. In particular, expressions derived from the model for eigenfrequencies at high symmetry points unambiguously predict the presence of a new type of Dirac-like cone at the Brillouin center, which is found to be the result of accidental degeneracy of the rotational and dipolar modes.

Lumped model for rotational modes in phononic crystals

KAUST Repository

Peng, Pai; Mei, Jun; Wu, Ying

2012-01-01

We present a lumped model for the rotational modes induced by the rotational motion of individual scatterers in two-dimensional phononic crystals comprised of square arrays of solid cylindrical scatterers in solid hosts. The model provides a physical interpretation of the origin of the rotational modes, reveals the important role played by the rotational motion in determining the band structure, and reproduces the dispersion relations in a certain range. The model increases the possibilities of manipulating wave propagation in phononic crystals. In particular, expressions derived from the model for eigenfrequencies at high symmetry points unambiguously predict the presence of a new type of Dirac-like cone at the Brillouin center, which is found to be the result of accidental degeneracy of the rotational and dipolar modes.

20 CFR 222.31 - Relationship as child for annuity and lump-sum payment purposes.

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2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Relationship as child for annuity and lump... UNDER THE RAILROAD RETIREMENT ACT FAMILY RELATIONSHIPS Relationship as Child § 222.31 Relationship as... the employee. For procedures on how a determination of the person's relationship to the employee is...

Determination and importance of temperature dependence of retention coefficient (RPHPLC) in QSAR model of nitrazepams' partition coefficient in bile acid micelles.

Science.gov (United States)

Posa, Mihalj; Pilipović, Ana; Lalić, Mladena; Popović, Jovan

2011-02-15

Linear dependence between temperature (t) and retention coefficient (k, reversed phase HPLC) of bile acids is obtained. Parameters (a, intercept and b, slope) of the linear function k=f(t) highly correlate with bile acids' structures. Investigated bile acids form linear congeneric groups on a principal component (calculated from k=f(t)) score plot that are in accordance with conformations of the hydroxyl and oxo groups in a bile acid steroid skeleton. Partition coefficient (K(p)) of nitrazepam in bile acids' micelles is investigated. Nitrazepam molecules incorporated in micelles show modified bioavailability (depo effect, higher permeability, etc.). Using multiple linear regression method QSAR models of nitrazepams' partition coefficient, K(p) are derived on the temperatures of 25°C and 37°C. For deriving linear regression models on both temperatures experimentally obtained lipophilicity parameters are included (PC1 from data k=f(t)) and in silico descriptors of the shape of a molecule while on the higher temperature molecular polarisation is introduced. This indicates the fact that the incorporation mechanism of nitrazepam in BA micelles changes on the higher temperatures. QSAR models are derived using partial least squares method as well. Experimental parameters k=f(t) are shown to be significant predictive variables. Both QSAR models are validated using cross validation and internal validation method. PLS models have slightly higher predictive capability than MLR models. Copyright © 2010 Elsevier B.V. All rights reserved.

Modelling of nonhomogeneous atmosphere in NPP containment using lumped-parameter model based on CFD calculations

International Nuclear Information System (INIS)

Kljenak, I.; Mavko, B.; Babic, M.

2005-01-01

Full text of publication follows: The modelling and simulation of atmosphere mixing and stratification in nuclear power plant containments is a topic, which is currently being intensely investigated. With the increase of computer power, it has now become possible to model these phenomena with a local instantaneous description, using so-called Computational Fluid Dynamics (CFD) codes. However, calculations with these codes still take relatively long times. An alternative faster approach, which is also being applied, is to model nonhomogeneous atmosphere with lumped-parameter codes by dividing larger control volumes into smaller volumes, in which conditions are modelled as homogeneous. The flow between smaller volumes is modelled using one-dimensional approaches, which includes the prescription of flow loss coefficients. However, some authors have questioned this approach, as it appears that atmosphere stratification may sometimes be well simulated only by adjusting flow loss coefficients to adequate 'artificial' values that are case-dependent. To start the resolution of this issue, a modelling of nonhomogeneous atmosphere with a lumped-parameter code is proposed, where the subdivision of a large volume into smaller volumes is based on results of CFD simulations. The basic idea is to use the results of a CFD simulation to define regions, in which the flow velocities have roughly the same direction. These regions are then modelled as control volumes in a lumped-parameter model. In the proposed work, this procedure was applied to a simulation of an experiment of atmosphere mixing and stratification, which was performed in the TOSQAN facility. The facility is located at the Institut de Radioprotection et de Surete Nucleaire (IRSN) in Saclay (France) and consists of a cylindrical vessel (volume: 7 m3), in which gases are injected. In the experiment, which was also proposed for the OECD/NEA International Standard Problem No.47, air was initially present in the vessel, and

DFT and 3D-QSAR Studies of Anti-Cancer Agents m-(4-Morpholinoquinazolin-2-yl) Benzamide Derivatives for Novel Compounds Design

Science.gov (United States)

Zhao, Siqi; Zhang, Guanglong; Xia, Shuwei; Yu, Liangmin

2018-06-01

As a group of diversified frameworks, quinazolin derivatives displayed a broad field of biological functions, especially as anticancer. To investigate the quantitative structure-activity relationship, 3D-QSAR models were generated with 24 quinazolin scaffold molecules. The experimental and predicted pIC50 values for both training and test set compounds showed good correlation, which proved the robustness and reliability of the generated QSAR models. The most effective CoMFA and CoMSIA were obtained with correlation coefficient r 2 ncv of 1.00 (both) and leave-one-out coefficient q 2 of 0.61 and 0.59, respectively. The predictive abilities of CoMFA and CoMSIA were quite good with the predictive correlation coefficients ( r 2 pred ) of 0.97 and 0.91. In addition, the statistic results of CoMFA and CoMSIA were used to design new quinazolin molecules.

QSAR Classification of ToxCast and Tox21 Chemicals on the Basis of Estrogen Receptor Assays (FutureToxII)

Science.gov (United States)

The ToxCast and Tox21 programs have tested ~8,200 chemicals in a broad screening panel of in vitro high-throughput screening (HTS) assays for estrogen receptor (ER) agonist and antagonist activity. The present work uses this large in vitro data set to develop in silico QSAR model...

Drop-on-Demand Inkjet Printhead Performance Enhancement by Dynamic Lumped Element Modeling for Printable Electronics Fabrication

Directory of Open Access Journals (Sweden)

Maowei He

2014-01-01

Full Text Available The major challenge in printable electronics fabrication is the print resolution and accuracy. In this paper, the dynamic lumped element model (DLEM is proposed to directly simulate an inkjet-printed nanosilver droplet formation process and used for predictively controlling jetting characteristics. The static lumped element model (LEM previously developed by the authors is extended to dynamic model with time-varying equivalent circuits to characterize nonlinear behaviors of piezoelectric printhead. The model is then used to investigate how performance of the piezoelectric ceramic actuator influences jetting characteristics of nanosilver ink. Finally, the proposed DLEM is applied to predict the printing quality using nanosilver ink. Experimental results show that, compared to other analytic models, the proposed DLEM has a simpler structure with the sufficient simulation and prediction accuracy.

A physically interpretable quantum-theoretic QSAR for some carbonic anhydrase inhibitors with diverse aromatic rings, obtained by a new QSAR procedure.

Science.gov (United States)

Clare, Brian W; Supuran, Claudiu T

2005-03-15

A QSAR based almost entirely on quantum theoretically calculated descriptors has been developed for a large and heterogeneous group of aromatic and heteroaromatic carbonic anhydrase inhibitors, using orbital energies, nodal angles, atomic charges, and some other intuitively appealing descriptors. Most calculations have been done at the B3LYP/6-31G* level of theory. For the first time we have treated five-membered rings by the same means that we have used for benzene rings in the past. Our flip regression technique has been expanded to encompass automatic variable selection. The statistical quality of the results, while not equal to those we have had with benzene derivatives, is very good considering the noncongeneric nature of the compounds. The most significant correlation was with charge on the atoms of the sulfonamide group, followed by the nodal orientation and the solvation energy calculated by COSMO and the charge polarization of the molecule calculated as the mean absolute Mulliken charge over all atoms.

Computing Fault-Containment Times of Self-Stabilizing Algorithms Using Lumped Markov Chains

Directory of Open Access Journals (Sweden)

Volker Turau

2018-05-01

Full Text Available The analysis of self-stabilizing algorithms is often limited to the worst case stabilization time starting from an arbitrary state, i.e., a state resulting from a sequence of faults. Considering the fact that these algorithms are intended to provide fault tolerance in the long run, this is not the most relevant metric. A common situation is that a running system is an a legitimate state when hit by a single fault. This event has a much higher probability than multiple concurrent faults. Therefore, the worst case time to recover from a single fault is more relevant than the recovery time from a large number of faults. This paper presents techniques to derive upper bounds for the mean time to recover from a single fault for self-stabilizing algorithms based on Markov chains in combination with lumping. To illustrate the applicability of the techniques they are applied to a new self-stabilizing coloring algorithm.

3D-QSAR (CoMFA, CoMSIA), molecular docking and molecular dynamics simulations study of 6-aryl-5-cyano-pyrimidine derivatives to explore the structure requirements of LSD1 inhibitors.

Science.gov (United States)

Ding, Lina; Wang, Zhi-Zheng; Sun, Xu-Dong; Yang, Jing; Ma, Chao-Ya; Li, Wen; Liu, Hong-Min

2017-08-01

Recently, Histone Lysine Specific Demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. And several small molecules as LSD1 inhibitors in different structures have been reported. In this work, we carried out a molecular modeling study on the 6-aryl-5-cyano-pyrimidine fragment LSD1 inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q 2 =0.802, r 2 ncv =0.979, and the best CoMSIA model has q 2 =0.799, r 2 ncv =0.982. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300K. All the results can provide us more useful information for our further drug design. Copyright © 2017. Published by Elsevier Ltd.

The discussion of descriptors for the QSAR model and molecular dynamics simulation of benzimidazole derivatives as corrosion inhibitors

International Nuclear Information System (INIS)

Li, Lu; Zhang, Xiuhui; Gong, Shida; Zhao, Hongxia; Bai, Yang; Li, Qianshu; Ji, Lin

2015-01-01

Graphical abstract: - Highlights: • Aromaticity is used as a descriptor in QSAR model to describe corrosion inhibition. • Improved calculation of I and A is correlated well with inhibition efficiencies. • Binding energies were calculated using a realistic corrosion environment. • Nonlinear QSAR model was built by support vector machine with radial basis function. • Six designed benzimidazole molecules are predicted with high inhibition efficiencies. - Abstract: The corrosion inhibition performances of 20 protonated benzimidazole derivatives were studied using theoretical methods. Nuclear Independent Chemical Shift (NICS), the measurement of aromaticity, demonstrated good correlation with inhibition efficiencies and was used as a descriptor. Binding energies were calculated on the basis of molecular dynamics simulations using a realistic corrosive environment. Some improved descriptors correlate well with experimental inhibition efficiencies. A reliable nonlinear quantitative structure–activity relationship model was constructed by a support vector machine approach. The correlation coefficient and root-mean-square error were 0.96 and 6.79%, respectively. Additionally, six new benzimidazole molecules were designed, and their inhibition efficiencies were predicted.

General 3D Lumped Thermal Model with Various Boundary Conditions for High Power IGBT Modules

DEFF Research Database (Denmark)

Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede

2016-01-01

Accurate thermal dynamics modeling of high power Insulated Gate Bipolar Transistor (IGBT) modules is important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated...... thermal behaviors in the IGBTs. In this paper, a new three-dimensional (3D) lumped thermal model is proposed, which can easily be characterized from Finite Element Methods (FEM) based simulation and acquire the thermal distribution in critical points. Meanwhile the boundary conditions including...... the cooling system and power losses are modeled in the 3D thermal model, which can be adapted to different real field applications of power electronic converters. The accuracy of the proposed thermal model is verified by experimental results....

Black holes as lumps of fluid

International Nuclear Information System (INIS)

Caldarelli, Marco M.; Dias, Oscar J.C.; Emparan, Roberto; Klemm, Dietmar

2009-01-01

The old suggestive observation that black holes often resemble lumps of fluid has recently been taken beyond the level of an analogy to a precise duality. We investigate aspects of this duality, and in particular clarify the relation between area minimization of the fluid vs. area maximization of the black hole horizon, and the connection between surface tension and curvature of the fluid, and surface gravity of the black hole. We also argue that the Rayleigh-Plateau instability in a fluid tube is the holographic dual of the Gregory-Laflamme instability of a black string. Associated with this fluid instability there is a rich variety of phases of fluid solutions that we study in detail, including in particular the effects of rotation. We compare them against the known results for asymptotically flat black holes finding remarkable agreement. Furthermore, we use our fluid results to discuss the unknown features of the gravitational system. Finally, we make some observations that suggest that asymptotically flat black holes may admit a fluid description in the limit of large number of dimensions.

Lumped-parameter modeling of PWR downcomer and pressurizer for LOCA conditions

International Nuclear Information System (INIS)

Rohatgi, U.S.; Saha, P.; Dubow, A.A.

1978-01-01

Two lumped-parameter models, one for a PWR downcomer and the other for a pressurizer, are presented. The models are based on the transient, nonhomogeneous, drift-flux description of two-phase flow, and are suitable for simulating a hypothetical LOCA condition. Effects of thermal nonequilibrium are incorporated in the downcomer model, whereas the pressurizer model can track the interfaces among various flow regimes. Semiimplicit numerical schemes are used for solution. Encouraging results have been obtained for both the models. (author)

Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign

Science.gov (United States)

Sliwoski, Gregory; Mendenhall, Jeffrey; Meiler, Jens

2016-03-01

Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance.

Lumped Parameter Models of the Central Nervous System for VIIP Research

Science.gov (United States)

Vera, J.; Mulugeta, L.; Nelson, E. S.; Raykin, J.; Feola, A.; Gleason, R.; Samuels, B.; Myers, J. G.

2015-01-01

INTRODUCTION: Current long-duration missions to the International Space Station and future exploration-class missions beyond low-Earth orbit, such as to Mars and asteroids, expose astronauts to increased risk of Visual Impairment and Intracranial Pressure (VIIP) syndrome [1]. It has been hypothesized that the headward shift of cerebral spinal fluid (CSF) and blood in microgravity may cause significant elevation of intracranial pressure (ICP), which in turn induces VIIP syndrome through biomechanical pathways [1, 2]. However, there is insufficient evidence to confirm this hypothesis. In this light, we are developing lumped-parameter models of fluid transport in the central nervous system (CNS) as a means to simulate the influence of microgravity on ICP. The CNS models will also be used in concert with the lumped parameter and finite element models of the eye described in the realted IWS abstracts submitted by Nelson et al., Feola et al. and Ethier et al. METHODS: We have developed a nine compartment CNS model (Figure 1) capable of both time-dependent and steady state fluid transport simulations, based on the works of Stevens et al. [3]. The breakdown of compartments within the model includes: vascular (3), CSF (2), brain (1) and extracranial (3). The boundary pressure in the Central Arteries [A] node is prescribed using an oscillating pressure function PA(t) simulating the carotid pulsatile pressure wave as developed by Linninger et al. [4]. For each time step, pressures are integrated through time using an adaptive-timestep 4th and 5th order Runga-Kutta solver. Once pressures are found, constitutive equations are used to solve for flowrates (Q) between each compartment. In addition to fluid flow between the different compartments, compliance (C) interactions between neighboring compartments are represented. We are also developing a second CNS model based on the works of Linninger et al. [4] which takes a more granular approach to represent the interactions of the

Lumped-Element Dynamic Electro-Thermal model of a superconducting magnet

Science.gov (United States)

Ravaioli, E.; Auchmann, B.; Maciejewski, M.; ten Kate, H. H. J.; Verweij, A. P.

2016-12-01

Modeling accurately electro-thermal transients occurring in a superconducting magnet is challenging. The behavior of the magnet is the result of complex phenomena occurring in distinct physical domains (electrical, magnetic and thermal) at very different spatial and time scales. Combined multi-domain effects significantly affect the dynamic behavior of the system and are to be taken into account in a coherent and consistent model. A new methodology for developing a Lumped-Element Dynamic Electro-Thermal (LEDET) model of a superconducting magnet is presented. This model includes non-linear dynamic effects such as the dependence of the magnet's differential self-inductance on the presence of inter-filament and inter-strand coupling currents in the conductor. These effects are usually not taken into account because superconducting magnets are primarily operated in stationary conditions. However, they often have significant impact on magnet performance, particularly when the magnet is subject to high ramp rates. Following the LEDET method, the complex interdependence between the electro-magnetic and thermal domains can be modeled with three sub-networks of lumped-elements, reproducing the electrical transient in the main magnet circuit, the thermal transient in the coil cross-section, and the electro-magnetic transient of the inter-filament and inter-strand coupling currents in the superconductor. The same simulation environment can simultaneously model macroscopic electrical transients and phenomena at the level of superconducting strands. The model developed is a very useful tool for reproducing and predicting the performance of conventional quench protection systems based on energy extraction and quench heaters, and of the innovative CLIQ protection system as well.

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization.

Science.gov (United States)

Bhargava, S; Adhikari, N; Amin, S A; Das, K; Gayen, S; Jha, T

2017-12-01

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r 2 = 0.806, Q 2 = 0.788 (split 1); r 2 = 0.842, Q 2 = 0.826 (split 2); r 2 = 0.774, Q 2 = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

A lumped model for rotational modes in periodic solid composites

KAUST Repository

Peng, Pai; Asiri, Sharefa M.; Zhang, Xiujuan; Li, Yan; Wu, Ying

2013-01-01

We present a lumped model to study the rotational modes in a type of two-dimensional periodic solid composites comprised of a square array of rubber-coated steel cylinders embedded in an epoxy matrix. The model captures the physical essence of rotational modes in such systems for various combinations of material parameters, and, therefore it is able to describe the transition behaviour when the system is gradually adjusted from an elastic metamaterial to an elastic phononic crystal. From the model, we can define a transition zone which separates the typical elastic metamaterials and the phononic crystals.

A lumped model for rotational modes in periodic solid composites

KAUST Repository

Peng, Pai

2013-10-01

We present a lumped model to study the rotational modes in a type of two-dimensional periodic solid composites comprised of a square array of rubber-coated steel cylinders embedded in an epoxy matrix. The model captures the physical essence of rotational modes in such systems for various combinations of material parameters, and, therefore it is able to describe the transition behaviour when the system is gradually adjusted from an elastic metamaterial to an elastic phononic crystal. From the model, we can define a transition zone which separates the typical elastic metamaterials and the phononic crystals.

Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.

Science.gov (United States)

Deeb, Omar; Shaik, Basheerulla; Agrawal, Vijay K

2014-10-01

Quantitative Structure-Activity Relationship (QSAR) models for binding affinity constants (log Ki) of 78 flavonoid ligands towards the benzodiazepine site of GABA (A) receptor complex were calculated using the machine learning methods: artificial neural network (ANN) and support vector machine (SVM) techniques. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. The descriptor selection and model building were performed with 10-fold cross-validation using the training data set. The SVM and MLR coefficient of determination values are 0.944 and 0.879, respectively, for the training set and are higher than those of ANN models. Though the SVM model shows improvement of training set fitting, the ANN model was superior to SVM and MLR in predicting the test set. Randomization test is employed to check the suitability of the models.

Analysis of direct contact membrane distillation based on a lumped-parameter dynamic predictive model

KAUST Repository

Karam, Ayman M.; Alsaadi, Ahmad Salem; Ghaffour, NorEddine; Laleg-Kirati, Taous-Meriem

2016-01-01

Membrane distillation (MD) is an emerging technology that has a great potential for sustainable water desalination. In order to pave the way for successful commercialization of MD-based water desalination techniques, adequate and accurate dynamical models of the process are essential. This paper presents the predictive capabilities of a lumped-parameter dynamic model for direct contact membrane distillation (DCMD) and discusses the results under wide range of steady-state and dynamic conditions. Unlike previous studies, the proposed model captures the time response of the spacial temperature distribution along the flow direction. It also directly solves for the local temperatures at the membrane interfaces, which allows to accurately model and calculate local flux values along with other intrinsic variables of great influence on the process, like the temperature polarization coefficient (TPC). The proposed model is based on energy and mass conservation principles and analogy between thermal and electrical systems. Experimental data was collected to validated the steady-state and dynamic responses of the model. The obtained results shows great agreement with the experimental data. The paper discusses the results of several simulations under various conditions to optimize the DCMD process efficiency and analyze its response. This demonstrates some potential applications of the proposed model to carry out scale up and design studies. © 2016

Analysis of direct contact membrane distillation based on a lumped-parameter dynamic predictive model

KAUST Repository

Karam, Ayman M.

2016-10-03

Membrane distillation (MD) is an emerging technology that has a great potential for sustainable water desalination. In order to pave the way for successful commercialization of MD-based water desalination techniques, adequate and accurate dynamical models of the process are essential. This paper presents the predictive capabilities of a lumped-parameter dynamic model for direct contact membrane distillation (DCMD) and discusses the results under wide range of steady-state and dynamic conditions. Unlike previous studies, the proposed model captures the time response of the spacial temperature distribution along the flow direction. It also directly solves for the local temperatures at the membrane interfaces, which allows to accurately model and calculate local flux values along with other intrinsic variables of great influence on the process, like the temperature polarization coefficient (TPC). The proposed model is based on energy and mass conservation principles and analogy between thermal and electrical systems. Experimental data was collected to validated the steady-state and dynamic responses of the model. The obtained results shows great agreement with the experimental data. The paper discusses the results of several simulations under various conditions to optimize the DCMD process efficiency and analyze its response. This demonstrates some potential applications of the proposed model to carry out scale up and design studies. © 2016

Building on a solid foundation: SAR and QSAR as a fundamental strategy to reduce animal testing.

Science.gov (United States)

Sullivan, K M; Manuppello, J R; Willett, C E

2014-01-01

The development of more efficient, ethical, and effective means of assessing the effects of chemicals on human health and the environment was a lifetime goal of Gilman Veith. His work has provided the foundation for the use of chemical structure for informing toxicological assessment by regulatory agencies the world over. Veith's scientific work influenced the early development of the SAR models in use today at the US Environmental Protection Agency. He was the driving force behind the Organisation for Economic Co-operation and Development QSAR Toolbox. Veith was one of a few early pioneers whose vision led to the linkage of chemical structure and biological activity as a means of predicting adverse apical outcomes (known as a mode of action, or an adverse outcome pathway approach), and he understood at an early stage the power that could be harnessed when combining computational and mechanistic biological approaches as a means of avoiding animal testing. Through the International QSAR Foundation he organized like-minded experts to develop non-animal methods and frameworks for the assessment of chemical hazard and risk for the benefit of public and environmental health. Avoiding animal testing was Gil's passion, and his work helped to initiate the paradigm shift in toxicology that is now rendering this feasible.

The effect of environmental factors on breast lumps of Egyptian women in different socioeconomic levels

International Nuclear Information System (INIS)

Salama, D.H.

2008-01-01

The environmental risk factors related to the breast tumors (lumps) are essential in order to build strategies to decrease cancer incidence and mortality among different socioeconomic and cultural backgrounds. A case control study of 70 cases and 52 controls were classified into high, middle and low socioeconomic classes. The results revealed significant increased risk of breast tumors among working females, having positive family history, married with lower mean parity, with higher consumption of fatty meals, lesser meat intake. Non significant risk factors were the social class, exposure to ionizing radiation, non lactating. wearing tight bra, consumption of vegetables and fruits, oral contraceptive pill users and exposure to outdoor air pollution or indoor pollution as floors and wall paintings. In conclusion, this study highlights the positive life style for egyptian women so they can prevent some of the environmental risks of breast tumors. Increasing the awareness of breast diseases and regular examination remains the corner stone for early detection management of breast lumps.

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

Energy Technology Data Exchange (ETDEWEB)

Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh [Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC (United States); Zhu, Hao [The Rutgers Center for Computational and Integrative Biology, Rutgers University, Camden, NJ (United States); Department of Chemistry, Rutgers University, Camden, NJ (United States); Afantitis, Antreas; Mouchlis, Varnavas D.; Melagraki, Georgia [NovaMechanics Ltd., Nicosia (Cyprus); Rusyn, Ivan, E-mail: iir@unc.edu [Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, NC (United States); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC (United States)

2013-10-01

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. �

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

International Nuclear Information System (INIS)

Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh; Zhu, Hao; Afantitis, Antreas; Mouchlis, Varnavas D.; Melagraki, Georgia; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R 2 = 0.71, STL R 2 = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R 2 = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results

Modeling Chronic Toxicity: A Comparison of Experimental Variability With (QSAR/Read-Across Predictions

Directory of Open Access Journals (Sweden)

Christoph Helma

2018-04-01

Full Text Available This study compares the accuracy of (QSAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended.

Lumped parameter modeling of a two-phase thermal-hydraulic channel with interface tracking

International Nuclear Information System (INIS)

Jo, J.H.; Kaufman, J.M.; Ruger, C.J.; Stein, S.

1978-01-01

A nonhomogenous, thermal nonequilibrium model for one-dimensional two-phase flow in a heated channel has been formulated in lumped parameter form. The channel is divided into a variable number of flow regimes separated by moving interfaces. The model can be used to predict the behavior of a LWR core and both primary and secondary sides of a steam generator under transient conditions. (author)

The Numerical Welding Simulation - Developments and Validation of Simplified and Bead Lumping Methods

International Nuclear Information System (INIS)

Baup, Olivier

2001-01-01

The aim of this work was to study the TIG multipass welding process on stainless steel, by means of numerical methods and then to work out simplified and bead lumping methods in order to reduce adjusting and realisation times of these calculations. A simulation was used as reference for the validation of these methods; after the presentation of the test series having led to the option choices of this calculation (2D generalised plane strains, elastoplastic model with an isotropic hardening, hardening restoration due to high temperatures), various simplifications were tried on a plate geometry. These simplifications related various modelling points with a correct plastic flow representation in the plate. The use of a reduced number of thermal fields characterising the bead deposit and a low number of tensile curves allow to obtain interesting results, decreasing significantly the Computing times. In addition various lumping bead methods have been studied and concerning both the shape and the thermic of the macro-deposits. The macro-deposit shapes studied are in 'L', or in layer or they represent two beads one on top of the other. Among these three methods, only those using a few number of lumping beads gave bad results since thermo-mechanical history was deeply modified near and inside the weld. Thereafter, simplified methods have been applied to a tubular geometry. On this new geometry, experimental measurements were made during welding, which allow a validation of the reference calculation. Simplified and reference calculations gave approximately the same stress fields as found on plate geometry. Finally, in the last part of this document a procedure for automatic data setting permitting to reduce significantly the calculation phase preparation is presented. It has been applied to the calculation of thick pipe welding in 90 beads; the results are compared with a simplified simulation realised by Framatome and with experimental measurements. A bead by

3D QSAR Studies of DAMNI Analogs as Possible Non-nucleoside Reverse Transcriptase Inhibitors

Directory of Open Access Journals (Sweden)

S. Ganguly

2008-01-01

Full Text Available The non-nucleoside inhibitors of HIV-1-reverse transcriptase (NNRTIs are an important class of drugs employed in antiviral therapy. Recently, a novel family of NNRTIs commonly referred to as 1-[2-diarylmethoxy] ethyl 2-methyl-5-nitroimidazoles (DAMNI derivatives have been discovered. The 3D-QSAR studies on DAMNI derivatives as NNRTIs was performed by comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA methods to determine the factors required for the activity of these compounds. The global minimum energy conformer of the template molecule 15, the most active molecule of the series, was obtained by simulated annealing method and used to build the structures of the molecules in the dataset. The combination of steric and electrostatic fields in CoMSIA gave the best results with cross-validated and conventional correlation coefficients of 0.654 and 0.928 respectively. The predictive ability of CoMFA and CoMSIA were determined using a test set of ten DAMNI derivatives giving predictive correlation coefficients of 0.92 and 0.98 respectively indicating good predictive power. Further, the robustness of the models was verified by bootstrapping analysis. The information obtained from CoMFA and CoMSIA 3D contour maps may be of utility in the design of more potent DAMNI analogs as NNRTIs in future.

Lumped Parameter Modeling for Rapid Vibration Response Prototyping and Test Correlation for Electronic Units

Science.gov (United States)

Van Dyke, Michael B.

2013-01-01

Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.

Flavonoids as Vasorelaxant Agents: Synthesis, Biological Evaluation and Quantitative Structure Activities Relationship (QSAR Studies

Directory of Open Access Journals (Sweden)

Yongzhou Hu

2011-09-01

Full Text Available A series of 2-(2-diethylamino-ethoxychalcone and 6-prenyl(or its isomers-flavanones 10a,b and 11a–g were synthesized and evaluated for their vasorelaxant activities against rat aorta rings pretreated with 1 μM phenylephrine (PE. Several compounds showed potent vasorelaxant activities. Compound 10a (EC50 = 7.6 μM, Emax = 93.1%, the most potent one, would be a promising structural template for development of novel and more efficient vasodilators. Further, 2D-QSAR analysis of compounds 10a,b and 11c-e as well as thirty previously synthesized flavonoids 1-3 and 12-38 using Enhanced Replacement Method-Multiple Linear Regression (ERM-MLR was further performed based on an optimal set of molecular descriptors (H5m, SIC2, DISPe, Mor03u and L3m, leading to a reliable model with good predictive ability (Rtrain2 = 0.839, Qloo2 = 0.733 and Rtest2 = 0.804. The results provide good insights into the structure- activity relationships of the target compounds.

MODEL QSAR SENYAWA FLUOROKUINOLON BARU SEBAGAI ZAT ANTIBAKTERI Salmonella thypimurium

Directory of Open Access Journals (Sweden)

Eva Vaulina

2006-11-01

Full Text Available Modelling of novel Fluoroquinolone derivates as antibacterial compund of Salmonella thypimurium was conducted. The research was done as an initial step in discovering some new Fluoroquinolone compounds which have higher activity to Salmonella thypimurium. There are 16 compunds that use as the material of the research and they already have antibacterial activity data that expressed in Minimal Inhibitory Concentration (MIC, mg/mL. Calculation was performed by semiempirical AM1 method. The QSAR model was determined by multilinear regression analysis, with Log MIC as dependent variable and the independent variables are atomic net charges of C5 (qC5 and C7 (qC7, dipole moment (m, polarizability (a, n-octanol-water coefficien partition (Log P, molecular weight (Mw, and surface area of van der Waals (AvdW. The relationship between Log MIC and the descriptors which performed by statistical analysis is:(Log MIC = -2.119 + 34.541(qC5 – 19.748(qC7 – 0.919polar + 1.170logP + 0.111(Mw – 0.003(Avdw, with n =16, r = 0.907, r2 = 0.822, SD = 0.288, F calc = 6.938, F table = 3.374 , F calc/F table = 2.056 and PRESS = 0.749. The research can obtain the new coumpounds that modified from compound number 16 (etil fluoroquinolone, MIC prediction = 0.0354 mg/mL, (etil fluoroquinlone fosfate, 2.84. 10-19mg/mL, and (isopropyl fluoroquinlone, 0.1085 mg/mL, and compound number 2 (m-nitro fluoroquinolone sulfonat, 1.32. 10-11mg/mL. This results can be suggested to synthesis step

Metastatic uterine leiomyosarcoma presenting as a breast lump.

LENUS (Irish Health Repository)

Sibartie, S

2009-01-31

BACKGROUND: It is uncommon to encounter a breast metastasis from an extramammary malignancy and even rarer from a uterine leiomyosarcoma. AIMS: We describe the third case report in the medical literature of a breast metastasis from a uterine leiomyosarcoma. METHODS: We report the management of a 56-year-old patient who presented with a breast lump 3 years after hysterectomy for a fibroid uterus. We conducted a literature review of breast leiomyosarcomas. RESULTS: The excision of the breast mass revealed a low-grade leiomyosarcoma. Radiographic examinations demonstrated metastases to the lung, liver, pelvis and bone. Retrospective pathology review of her uterus identified a small focus of leiomyosarcoma. She received chemotherapy and palliative radiotherapy but passed away within few months. CONCLUSION: Metastasis to the breast from a non-breast primary is generally a sign of disseminated disease and; thus, a poor prognostic indicator.

Study of Pellets and Lumps as Raw Materials in Silicon Production from Quartz and Silicon Carbide

Science.gov (United States)

Dal Martello, E.; Tranell, G.; Gaal, S.; Raaness, O. S.; Tang, K.; Arnberg, L.

2011-10-01

The use of high-purity carbon and quartz raw materials reduces the need for comprehensive refining steps after the silicon has been produced carbothermically in the electric reduction furnace. The current work aims at comparing the reaction mechanisms and kinetics occurring in the inner part of the reduction furnace when pellets or lumpy charge is used, as well as the effect of the raw material mix. Laboratory-scale carbothermic reduction experiments have been carried out in an induction furnace. High-purity silicon carbide and two different high-purity hydrothermal quartzes were charged as raw materials at different molar ratios. The charge was in the form of lumps (size, 2-5 mm) or as powder (size, 10-20 μm), mixed and agglomerated as pellets (size, 1-3 mm) and reacted at 2273 K (2000 °C). The thermal properties of the quartzes were measured also by heating a small piece of quartz in CO atmosphere. The investigated quartzes have different reactivity in reducing atmosphere. The carbothermal reduction experiments show differences in the reacted charge between pellets and lumps as charge material. Solid-gas reactions take place from the inside of the pellets porosity, whereas reactions in lumps occur topochemically. Silicon in pellets is produced mainly in the rim zone. Larger volumes of silicon have been found when using lumpy charge. More SiO is produced when using pellets than for lumpy SiO2 for the same molar ratio and heating conditions. The two SiC polytypes used in the carbothermal reduction experiments as carbon reductants presented different reactivity.

A Combination of 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation Studies of Benzimidazole-Quinolinone Derivatives as iNOS Inhibitors

Directory of Open Access Journals (Sweden)

Peixun Liu

2012-09-01

Full Text Available Inducible Nitric Oxide Synthase (iNOS has been involved in a variety of diseases, and thus it is interesting to discover and optimize new iNOS inhibitors. In previous studies, a series of benzimidazole-quinolinone derivatives with high inhibitory activity against human iNOS were discovered. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR, molecular docking and molecular dynamics (MD simulation approaches were applied to investigate the functionalities of active molecular interaction between these active ligands and iNOS. A QSAR model with R2 of 0.9356, Q2 of 0.8373 and Pearson-R value of 0.9406 was constructed, which presents a good predictive ability in both internal and external validation. Furthermore, a combined analysis incorporating the obtained model and the MD results indicates: (1 compounds with the proper-size hydrophobic substituents at position 3 in ring-C (R3 substituent, hydrophilic substituents near the X6 of ring-D and hydrophilic or H-bond acceptor groups at position 2 in ring-B show enhanced biological activities; (2 Met368, Trp366, Gly365, Tyr367, Phe363, Pro344, Gln257, Val346, Asn364, Met349, Thr370, Glu371 and Tyr485 are key amino acids in the active pocket, and activities of iNOS inhibitors are consistent with their capability to alter the position of these important residues, especially Glu371 and Thr370. The results provide a set of useful guidelines for the rational design of novel iNOS inhibitors.

Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development.

Science.gov (United States)

Tetko, Igor V; Maran, Uko; Tropsha, Alexander

2017-03-01

Thousands of (Quantitative) Structure-Activity Relationships (Q)SAR models have been described in peer-reviewed publications; however, this way of sharing seldom makes models available for the use by the research community outside of the developer's laboratory. Conversely, on-line models allow broad dissemination and application representing the most effective way of sharing the scientific knowledge. Approaches for sharing and providing on-line access to models range from web services created by individual users and laboratories to integrated modeling environments and model repositories. This emerging transition from the descriptive and informative, but "static", and for the most part, non-executable print format to interactive, transparent and functional delivery of "living" models is expected to have a transformative effect on modern experimental research in areas of scientific and regulatory use of (Q)SAR models. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthesis, antifungal activity, and QSAR studies of 1,6-dihydropyrimidine derivatives

Directory of Open Access Journals (Sweden)

Chirag Rami

2013-01-01

Full Text Available Introduction: A practical synthesis of pyrimidinone would be very helpful for chemists because pyrimidinone is found in many bioactive natural products and exhibits a wide range of biological properties. The biological significance of pyrimidine derivatives has led us to the synthesis of substituted pyrimidine. Materials and Methods: With the aim of developing potential antimicrobials, new series of 5-cyano-6-oxo-1,6-dihydro-pyrimidine derivatives namely 2-(5-cyano-6-oxo-4-substituted (aryl-1,6-dihydropyrimidin-2-ylthio-N-substituted (phenyl acetamide (C1-C41 were synthesized and characterized by Fourier transform infrared spectroscopy (FTIR, mass analysis, and proton nuclear magnetic resonance ( 1 H NMR. All the compounds were screened for their antifungal activity against Candida albicans (MTCC, 227. Results and Discussion: Quantitative structure activity relationship (QSAR studies of a series of 1,6-dihydro-pyrimidine were carried out to study various structural requirements for fungal inhibition. Various lipophilic, electronic, geometric, and spatial descriptors were correlated with antifungal activity using genetic function approximation. Developed models were found predictive as indicated by their square of predictive regression values (r 2pred and their internal and external cross-validation. Study reveals that CHI_3_C, Molecular_SurfaceArea, and Jurs_DPSA_1 contributed significantly to the activity along with some electronic, geometric, and quantum mechanical descriptors. Conclusion: A careful analysis of the antifungal activity data of synthesized compounds revealed that electron withdrawing substitution on N-phenyl acetamide ring of 1,6-dihydropyrimidine moiety possess good activity.

DESIGN OF LOW CYTOTOXICITY DIARYLANILINE DERIVATIVES BASED ON QSAR RESULTS: AN APPLICATION OF ARTIFICIAL NEURAL NETWORK MODELLING

Directory of Open Access Journals (Sweden)

Ihsanul Arief

2016-11-01

Full Text Available Study on cytotoxicity of diarylaniline derivatives by using quantitative structure-activity relationship (QSAR has been done. The structures and cytotoxicities of  diarylaniline derivatives were obtained from the literature. Calculation of molecular and electronic parameters was conducted using Austin Model 1 (AM1, Parameterized Model 3 (PM3, Hartree-Fock (HF, and density functional theory (DFT methods.  Artificial neural networks (ANN analysis used to produce the best equation with configuration of input data-hidden node-output data = 5-8-1, value of r2 = 0.913; PRESS = 0.069. The best equation used to design and predict new diarylaniline derivatives.  The result shows that compound N1-(4′-Cyanophenyl-5-(4″-cyanovinyl-2″,6″-dimethyl-phenoxy-4-dimethylether benzene-1,2-diamine is the best-proposed compound with cytotoxicity value (CC50 of 93.037 μM.

Combining molecular docking and QSAR studies for modeling the anti-tyrosinase activity of aromatic heterocycle thiosemicarbazone analogues

Science.gov (United States)

Dong, Huanhuan; Liu, Jing; Liu, Xiaoru; Yu, Yanying; Cao, Shuwen

2018-01-01

A collection of thirty-six aromatic heterocycle thiosemicarbazone analogues presented a broad span of anti-tyrosinase activities were designed and obtained. A robust and reliable two-dimensional quantitative structure-activity relationship model, as evidenced by the high q2 and r2 values (0.848 and 0.893, respectively), was gained based on the analogues to predict the quantitative chemical-biological relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend on molecular shape and orbital energy. Substituents brought out large ovality and high highest-occupied molecular orbital energy values helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and inhibition mechanism. Based on these, two novel tyrosinase inhibitors O04 and O05 with predicted IC50 of 0.5384 and 0.8752 nM were designed and suggested for further research.

Advertising Pricing Models in Media Markets: Lump-Sum versus Per-Consumer Charges

OpenAIRE

Helmut Dietl; Markus Lang; Panlang Lin

2012-01-01

This paper develops a model of asymmetric competition between a pay and a free media platform. The pay media platform generates revenues from media consumers through subscription fees, while the free media platform generates revenues from charging advertisers either on a lump-sum basis (regime A) or on a per-consumer basis (regime B). We show that the free platform produces a higher advertising level and attracts more consumers in regime A than B although advertisers must pay more for ads and...

DAT/SERT Selectivity of Flexible GBR 12909 Analogs Modeled Using 3D-QSAR Methods

Science.gov (United States)

Gilbert, Kathleen M.; Boos, Terrence L.; Dersch, Christina M.; Greiner, Elisabeth; Jacobson, Arthur E.; Lewis, David; Matecka, Dorota; Prisinzano, Thomas E.; Zhang, Ying; Rothman, Richard B.; Rice, Kenner C.; Venanzi, Carol A.

2007-01-01

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pKi (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q2 = 0.508, standard error of prediction = 0.601, two components, r2 = 0.685, standard error of estimate = 0.481, F value = 39, percent steric contribution = 65, and percent electrostatic contribution = 35. A CoMFA contour map identified areas of the molecule that affect pKi (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules. PMID:17127069

Predictive QSAR modelling of algal toxicity of ionic liquids and its interspecies correlation with Daphnia toxicity.

Science.gov (United States)

Roy, Kunal; Das, Rudra Narayan; Popelier, Paul L A

2015-05-01

Predictive toxicology using chemometric tools can be very useful in order to fill the data gaps for ionic liquids (ILs) with limited available experimental toxicity information, in view of their growing industrial uses. Though originally promoted as green chemicals, ILs have now been shown to possess considerable toxicity against different ecological endpoints. Against this background, quantitative structure-activity relationship (QSAR) models have been developed here for the toxicity of ILs against the green algae Scenedesmus vacuolatus using computed descriptors with definite physicochemical meaning. The final models emerged from E-state indices, extended topochemical atom (ETA) indices and quantum topological molecular similarity (QTMS) indices. The developed partial least squares models support the established mechanism of toxicity of ionic liquids in terms of a surfactant action of cations and chaotropic action of anions. The models have been developed within the guidelines of the Organization of Economic Co-operation and Development (OECD) for regulatory QSAR models, and they have been validated both internally and externally using multiple strategies and also tested for applicability domain. A preliminary attempt has also been made, for the first time, to develop interspecies quantitative toxicity-toxicity relationship (QTTR) models for the algal toxicity of ILs with Daphnia toxicity, which should be interesting while predicting toxicity of ILs for an endpoint when the data for the other are available.

Measurement of Hydrologic Streamflow Metrics and Estimation of Streamflow with Lumped Parameter Models in a Managed Lake System, Sebago Lake, Maine

Science.gov (United States)

Reeve, A. S.; Martin, D.; Smith, S. M.

2013-12-01

Surface waters within the Sebago Lake watershed (southern Maine, USA) provide a variety of economically and intrinsically valuable recreational, commercial and environmental services. Different stakeholder groups for the 118 km2 Sebago Lake and surrounding watershed advocate for different lake and watershed management strategies, focusing on the operation of a dam at the outflow from Sebago Lake. While lake level in Sebago Lake has been monitored for over a century, limited data is available on the hydrologic processes that drive lake level and therefore impact how dam operation (and other changes to the region) will influence the hydroperiod of the lake. To fill this information gap several tasks were undertaken including: 1) deploying data logging pressure transducers to continuously monitor stream stage in nine tributaries, 2) measuring stream discharge at these sites to create rating curves for the nine tributaries, and using the resulting continuous discharge records to 3) calibrate lumped parameter computer models based on the GR4J model, modified to include a degree-day snowmelt routine. These lumped parameter models have been integrated with a simple lake water-balance model to estimate lake level and its response to different scenarios including dam management strategies. To date, about three years of stream stage data have been used to estimate stream discharge in all monitored tributaries (data collection is ongoing). Baseflow separation indices (BFI) for 2010 and 2011 using the USGS software PART and the Eckhart digital filter in WHAT range from 0.80-0.86 in the Crooked River and Richmill Outlet,followed by Northwest (0.75) and Muddy (0.53-0.56) Rivers, with the lowest BFI measured in Sticky River (0.41-0.56). The BFI values indicate most streams have significant groundwater (or other storage) inputs. The lumped parameter watershed model has been calibrated for four streams (Nash-Sutcliffe = 0.4 to 0.9), with the other major tributaries containing

Cultural factors associated with the management of breast lumps amongst Xhosa women

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Nosipho Mdondolo

2003-11-01

Full Text Available A qualitative research design and an ethno-nursing research method were used to identify cultural factors influencing Xhosa women’s health seeking behaviours associated with breast lumps. Opsomming ’n Kwalitatiewe navorsingsontwerp en ’n etnoverpleegkundige navorsingsmetode is gebruik. Die doel was om te bepaal watter kulturele faktore Xhosa vroue se strewe na welstand, wat in verband staan met ’n borsvergroeisel, beïnvloed. *Please note: This is a reduced version of the abstract. Please refer to PDF for full text.

Recent advances in segmented gamma scanner analysis

International Nuclear Information System (INIS)

Sprinkle, J.K. Jr.; Hsue, S.T.

1987-01-01

The segmented gamma scanner (SGS) is used in many facilities to assay low-density scrap and waste generated in the facilities. The procedures for using the SGS can cause a negative bias if the sample does not satisfy the assumptions made in the method. Some process samples do not comply with the assumptions. This paper discusses the effect of the presence of lumps on the SGS assay results, describes a method to detect the presence of lumps, and describes an approach to correct for the lumps. Other recent advances in SGS analysis are also discussed

QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification

KAUST Repository

Sudhakaran, Sairam; Amy, Gary L.

2013-01-01

. In this study, quantitative structure activity relationships (QSAR) models for O3 and AOP processes were developed, and rate constants, kOH and kO3, were predicted based on target compound properties. The kO3 and kOH values ranged from 5 * 10-4 to 105 M-1s-1

New Procedure to Develop Lumped Kinetic Models for Heavy Fuel Oil Combustion

KAUST Repository

Han, Yunqing

2016-09-20

A new procedure to develop accurate lumped kinetic models for complex fuels is proposed, and applied to the experimental data of the heavy fuel oil measured by thermogravimetry. The new procedure is based on the pseudocomponents representing different reaction stages, which are determined by a systematic optimization process to ensure that the separation of different reaction stages with highest accuracy. The procedure is implemented and the model prediction was compared against that from a conventional method, yielding a significantly improved agreement with the experimental data. © 2016 American Chemical Society.

SURVIVING OF COMMERCIAL PROBIOTIC STRAIN Lactobacillus rhamnosus GG IN SLOVAK COW LUMP CHEESE EXPERIMENTALLY INOCULATED WITH Listeria innocua

Directory of Open Access Journals (Sweden)

Andrea Lauková

2014-08-01

Full Text Available Cow lump cheese represents a traditional Slovak cheese. It belongs to fresh types of cheeses. The aim of this study was to test surviving of commercial probiotic strain Lactobacillus rhamnosus GG in cow lump cheese experimentally infected with L. innocua; (listeriae are contaminants and to check the suitability of GG strain as additive for this product. The counts of GG strain in cow lump cheeses were well balanced during whole experiment. It was found in the counts from 5.48 ± 0.15 to 7.77 ±1.50 log10 cfu/g. Its maximum in cheese was 7.77 ± 1.30 log10 cfu/g on day 7 with stability up to day 14. The identity of GG strain isolated from cheeses was confirmed by PCR. The counts of other lactic acid bacteria were also well balanced during the whole experiment in the experimental cheeses with stability up to day 14. Only in E1/GG cheese, the highest number of LAB was detected (10.60 ±1.26 log10 cfu/g. The count of L. innocua LMG 13568 was not influenced. The pH and lactic acid values were not negatively influenced. Visually, the GG cheese provided a good structure (consistency.It can be disputed that shelf-life of the product could be maintained by this way and/or the product itself with GG strain can be consumed as afunctional food or to serve as a probiotic strain carrier.

(Q)SAR tools for priority setting: A case study with printed paper and board food contact material substances.

Science.gov (United States)

Van Bossuyt, Melissa; Van Hoeck, Els; Raitano, Giuseppa; Manganelli, Serena; Braeken, Els; Ates, Gamze; Vanhaecke, Tamara; Van Miert, Sabine; Benfenati, Emilio; Mertens, Birgit; Rogiers, Vera

2017-04-01

Over the last years, more stringent safety requirements for an increasing number of chemicals across many regulatory fields (e.g. industrial chemicals, pharmaceuticals, food, cosmetics, …) have triggered the need for an efficient screening strategy to prioritize the substances of highest concern. In this context, alternative methods such as in silico (i.e. computational) techniques gain more and more importance. In the current study, a new prioritization strategy for identifying potentially mutagenic substances was developed based on the combination of multiple (quantitative) structure-activity relationship ((Q)SAR) tools. Non-evaluated substances used in printed paper and board food contact materials (FCM) were selected for a case study. By applying our strategy, 106 out of the 1723 substances were assigned 'high priority' as they were predicted mutagenic by 4 different (Q)SAR models. Information provided within the models allowed to identify 53 substances for which Ames mutagenicity prediction already has in vitro Ames test results. For further prioritization, additional support could be obtained by applying local i.e. specific models, as demonstrated here for aromatic azo compounds, typically found in printed paper and board FCM. The strategy developed here can easily be applied to other groups of chemicals facing the same need for priority ranking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating the fates of organic contaminants in an aquifer using QSAR.

Science.gov (United States)

Lim, Seung Joo; Fox, Peter

2013-01-01

The quantitative structure activity relationship (QSAR) model, BIOWIN, was modified to more accurately estimate the fates of organic contaminants in an aquifer. The predictions from BIOWIN were modified to include oxidation and sorption effects. The predictive model therefore included the effects of sorption, biodegradation, and oxidation. A total of 35 organic compounds were used to validate the predictive model. The majority of the ratios of predicted half-life to measured half-life were within a factor of 2 and no ratio values were greater than a factor of 5. In addition, the accuracy of estimating the persistence of organic compounds in the sub-surface was superior when modified by the relative fraction adsorbed to the solid phase, 1/Rf, to that when modified by the remaining fraction of a given compound adsorbed to a solid, 1 - fs.

QSAR and docking studies of anthraquinone derivatives by similarity cluster prediction.

Science.gov (United States)

Harsa, Alexandra M; Harsa, Teodora E; Diudea, Mircea V

2016-01-01

Forty anthraquinone derivatives have been downloaded from PubChem database and investigated in a quantitative structure-activity relationships (QSAR) study. The models describing log P and LD50 of this set were built up on the hypermolecule scheme that mimics the investigated receptor space; the models were validated by the leave-one-out procedure, in the external test set and in a new version of prediction by using similarity clusters. Molecular docking approach using Lamarckian Genetic Algorithm was made on this class of anthraquinones with respect to 3Q3B receptor. The best scored molecules in the docking assay were used as leaders in the similarity clustering procedure. It is demonstrated that the LD50 data of this set of anthraquinones are related to the binding energies of anthraquinone ligands to the 3Q3B receptor.

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities.

Science.gov (United States)

Lima, Marilia N N; Melo-Filho, Cleber C; Cassiano, Gustavo C; Neves, Bruno J; Alves, Vinicius M; Braga, Rodolpho C; Cravo, Pedro V L; Muratov, Eugene N; Calit, Juliana; Bargieri, Daniel Y; Costa, Fabio T M; Andrade, Carolina H

2018-01-01

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium , affecting more than 200 million people worldwide every year and leading to about a half million deaths. Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds. Given that the inhibition of deoxyuridine triphosphatase of Plasmodium falciparum ( Pf dUTPase) induces wrong insertions in plasmodial DNA and consequently leading the parasite to death, this enzyme is considered an attractive antimalarial drug target. Using a combi-QSAR (quantitative structure-activity relationship) approach followed by virtual screening and in vitro experimental evaluation, we report herein the discovery of novel chemical scaffolds with in vitro potency against asexual blood stages of both P. falciparum multidrug-resistant and sensitive strains and against sporogonic development of P. berghei . We developed 2D- and 3D-QSAR models using a series of nucleosides reported in the literature as Pf dUTPase inhibitors. The best models were combined in a consensus approach and used for virtual screening of the ChemBridge database, leading to the identification of five new virtual Pf dUTPase inhibitors. Further in vitro testing on P. falciparum multidrug-resistant (W2) and sensitive (3D7) parasites showed that compounds LabMol-144 and LabMol-146 demonstrated fair activity against both strains and presented good selectivity versus mammalian cells. In addition, LabMol-144 showed good in vitro inhibition of P. berghei ookinete formation, demonstrating that hit-to-lead optimization based on this compound may also lead to new antimalarials with transmission blocking activity.

Some Phthalocyanine and Naphthalocyanine Derivatives as Corrosion Inhibitors for Aluminium in Acidic Medium: Experimental, Quantum Chemical Calculations, QSAR Studies and Synergistic Effect of Iodide Ions

Directory of Open Access Journals (Sweden)

Masego Dibetsoe

2015-08-01

Full Text Available The effects of seven macrocyclic compounds comprising four phthalocyanines (Pcs namely 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine (Pc1, 2,3,9,10,16,17,23,24-octakis(octyloxy-29H,31H-phthalocyanine (Pc2, 2,9,16,23-tetra-tert-butyl-29H,31H-phthalocyanine (Pc3 and 29H,31H-phthalocyanine (Pc4, and three naphthalocyanines namely 5,9,14,18,23,27,32,36-octabutoxy-2,3-naphthalocyanine (nPc1, 2,11,20,29-tetra-tert-butyl-2,3-naphthalocyanine (nPc2 and 2,3-naphthalocyanine (nP3 were investigated on the corrosion of aluminium (Al in 1 M HCl using a gravimetric method, potentiodynamic polarization technique, quantum chemical calculations and quantitative structure activity relationship (QSAR. Synergistic effects of KI on the corrosion inhibition properties of the compounds were also investigated. All the studied compounds showed appreciable inhibition efficiencies, which decrease with increasing temperature from 30 °C to 70 °C. At each concentration of the inhibitor, addition of 0.1% KI increased the inhibition efficiency compared to the absence of KI indicating the occurrence of synergistic interactions between the studied molecules and I− ions. From the potentiodynamic polarization studies, the studied Pcs and nPcs are mixed type corrosion inhibitors both without and with addition of KI. The adsorption of the studied molecules on Al surface obeys the Langmuir adsorption isotherm, while the thermodynamic and kinetic parameters revealed that the adsorption of the studied compounds on Al surface is spontaneous and involves competitive physisorption and chemisorption mechanisms. The experimental results revealed the aggregated interactions between the inhibitor molecules and the results further indicated that the peripheral groups on the compounds affect these interactions. The calculated quantum chemical parameters and the QSAR results revealed the possibility of strong interactions between the studied inhibitors and metal surface. QSAR

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

Science.gov (United States)

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

2005-01-13

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

Environmental risk assessment of selected organic chemicals based on TOC test and QSAR estimation models.

Science.gov (United States)

Chi, Yulang; Zhang, Huanteng; Huang, Qiansheng; Lin, Yi; Ye, Guozhu; Zhu, Huimin; Dong, Sijun

2018-02-01

Environmental risks of organic chemicals have been greatly determined by their persistence, bioaccumulation, and toxicity (PBT) and physicochemical properties. Major regulations in different countries and regions identify chemicals according to their bioconcentration factor (BCF) and octanol-water partition coefficient (Kow), which frequently displays a substantial correlation with the sediment sorption coefficient (Koc). Half-life or degradability is crucial for the persistence evaluation of chemicals. Quantitative structure activity relationship (QSAR) estimation models are indispensable for predicting environmental fate and health effects in the absence of field- or laboratory-based data. In this study, 39 chemicals of high concern were chosen for half-life testing based on total organic carbon (TOC) degradation, and two widely accepted and highly used QSAR estimation models (i.e., EPI Suite and PBT Profiler) were adopted for environmental risk evaluation. The experimental results and estimated data, as well as the two model-based results were compared, based on the water solubility, Kow, Koc, BCF and half-life. Environmental risk assessment of the selected compounds was achieved by combining experimental data and estimation models. It was concluded that both EPI Suite and PBT Profiler were fairly accurate in measuring the physicochemical properties and degradation half-lives for water, soil, and sediment. However, the half-lives between the experimental and the estimated results were still not absolutely consistent. This suggests deficiencies of the prediction models in some ways, and the necessity to combine the experimental data and predicted results for the evaluation of environmental fate and risks of pollutants. Copyright © 2016. Published by Elsevier B.V.

Unusual Presentation of Hydatidosis - Neck Lump Causing Costo-Vertebral Erosion.

Science.gov (United States)

Alam, Mehtab; Hasan, Syed-Abrar; Hashmi, Shahab-Farkhund

2016-09-01

Hydatid disease caused by larval stage of Echinococcus has been recognized endemically in many countries. Liver and lungs are the most commonly affected organs. Involvement of the head and neck region is rare and bony erosion due to hydatidosis is even rarer. We report a case of a 17-year-old girl from a poor socio-economic background who presented with a right sided supraclavicular lump, which after surgical excision and histopathological examination was diagnosed as hydatid cyst of neck. Because of its rarity in the neck region, primary diagnosis of hydatid cyst is overlooked and usually not included in the differential diagnosis of cystic neck swellings. A high index of suspicion is necessary to diagnose hydatid disease in an unusual location even in endemic areas.

Foreign body granuloma in the anterior abdominal wall mimicking an acute appendicular lump and induced by a translocated copper-T intrauterine contraceptive device: a case report

Directory of Open Access Journals (Sweden)

Ansari Maulana Mohammed

2009-04-01

Full Text Available Abstract Introduction Intrauterine contraceptive devices may at times perforate and migrate to adjacent organs. Such uterine perforation usually passes unnoticed with development of potentially serious complications. Case presentation A 25-year-old woman of North Indian origin presented with an acute tender lump in the right iliac fossa. The lump was initially thought to be an appendicular lump and treated conservatively. Resolution of the lump was incomplete. On exploratory laparotomy, a hard suspicious mass was found in the anterior abdominal wall of the right iliac fossa. Wide excision and bisection of the mass revealed a copper-T embedded inside. Examination of the uterus did not show any evidence of perforation. The next day, the patient gave a history of past copper-T Intrauterine contraceptive device insertion. Conclusions Copper-T insertion is one of the simplest contraceptive methods but its neglect with inadequate follow-up may lead to uterine perforation and extra-uterine migration. Regular self-examination for the "threads" supplemented with abdominal X-ray and/or ultrasound in the follow-up may detect copper-T migration early. To the best of our knowledge, this is the first report of intrauterine contraceptive device migration to the anterior abdominal wall of the right iliac fossa.

The use of QSAR methods for determination of n-octanol/water partition coefficient using the example of hydroxyester HE-1

Science.gov (United States)

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 use of QSAR methods for determination of n-octanol/water partition coefficient using the example of hydroxyester HE-1

Directory of Open Access Journals (Sweden)

Guziałowska-Tic Joanna

2017-01-01

Full Text Available 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%.

Optimization of PAM-4 transmitters based on lumped silicon photonic MZMs for high-speed short-reach optical links.

Science.gov (United States)

Zhou, Shiyu; Wu, Hsin-Ta; Sadeghipour, Khosrov; Scarcella, Carmelo; Eason, Cormac; Rensing, Marc; Power, Mark J; Antony, Cleitus; O'Brien, Peter; Townsend, Paul D; Ossieur, Peter

2017-02-20

We demonstrate how to optimize the performance of PAM-4 transmitters based on lumped Silicon Photonic Mach-Zehnder Modulators (MZMs) for short-reach optical links. Firstly, we analyze the trade-off that occurs between extinction ratio and modulation loss when driving an MZM with a voltage swing less than the MZM's Vπ. This is important when driver circuits are realized in deep submicron CMOS process nodes. Next, a driving scheme based upon a switched capacitor approach is proposed to maximize the achievable bandwidth of the combined lumped MZM and CMOS driver chip. This scheme allows the use of lumped MZM for high speed optical links with reduced RF driver power consumption compared to the conventional approach of driving MZMs (with transmission line based electrodes) with a power amplifier. This is critical for upcoming short-reach link standards such as 400Gb/s 802.3 Ethernet. The driver chip was fabricated using a 65nm CMOS technology and flip-chipped on top of the Silicon Photonic chip (fabricated using IMEC's ISIPP25G technology) that contains the MZM. Open eyes with 4dB extinction ratio for a 36Gb/s (18Gbaud) PAM-4 signal are experimentally demonstrated. The electronic driver chip has a core area of only 0.11mm2 and consumes 236mW from 1.2V and 2.4V supply voltages. This corresponds to an energy efficiency of 6.55pJ/bit including Gray encoder and retiming, or 5.37pJ/bit for the driver circuit only.

Biochemical interpretation of quantitative structure-activity relationships (QSAR) for biodegradation of N-heterocycles: a complementary approach to predict biodegradability.

Science.gov (United States)

Philipp, Bodo; Hoff, Malte; Germa, Florence; Schink, Bernhard; Beimborn, Dieter; Mersch-Sundermann, Volker

2007-02-15

Prediction of the biodegradability of organic compounds is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. We combined quantitative structure-activity relationships (QSAR) with the systematic collection of biochemical knowledge to establish rules for the prediction of aerobic biodegradation of N-heterocycles. Validated biodegradation data of 194 N-heterocyclic compounds were analyzed using the MULTICASE-method which delivered two QSAR models based on 17 activating (OSAR 1) and on 16 inactivating molecular fragments (GSAR 2), which were statistically significantly linked to efficient or poor biodegradability, respectively. The percentages of correct classifications were over 99% for both models, and cross-validation resulted in 67.9% (GSAR 1) and 70.4% (OSAR 2) correct predictions. Biochemical interpretation of the activating and inactivating characteristics of the molecular fragments delivered plausible mechanistic interpretations and enabled us to establish the following biodegradation rules: (1) Target sites for amidohydrolases and for cytochrome P450 monooxygenases enhance biodegradation of nonaromatic N-heterocycles. (2) Target sites for molybdenum hydroxylases enhance biodegradation of aromatic N-heterocycles. (3) Target sites for hydratation by an urocanase-like mechanism enhance biodegradation of imidazoles. Our complementary approach represents a feasible strategy for generating concrete rules for the prediction of biodegradability of organic compounds.

Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

Science.gov (United States)

Jothiprakash, V.; Magar, R. B.

2012-07-01

SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

Determination of heat flows inside turbochargers by means of a one dimensional lumped model

OpenAIRE

Olmeda González, Pablo Cesar; Dolz Ruiz, Vicente; Arnau Martínez, Francisco José; Reyes Belmonte, Miguel Angel

2013-01-01

In the present paper, a methodology to calculate the heat fluxes inside a turbocharger from diesel passenger car is presented. The heat transfer phenomenon is solved by using a one dimensional lumped model that takes into account both the heat fluxes between the different turbocharger elements, as well as the heat fluxes between the working fluids and the turbocharger elements. This heat transfer study is supported by the high temperature differences between the working fluids passing thr...

5D-QSAR for spirocyclic sigma1 receptor ligands by Quasar receptor surface modeling.

Science.gov (United States)

Oberdorf, Christoph; Schmidt, Thomas J; Wünsch, Bernhard

2010-07-01

Based on a contiguous and structurally as well as biologically diverse set of 87 sigma(1) ligands, a 5D-QSAR study was conducted in which a quasi-atomistic receptor surface modeling approach (program package Quasar) was applied. The superposition of the ligands was performed with the tool Pharmacophore Elucidation (MOE-package), which takes all conformations of the ligands into account. This procedure led to four pharmacophoric structural elements with aromatic, hydrophobic, cationic and H-bond acceptor properties. Using the aligned structures a 3D-model of the ligand binding site of the sigma(1) receptor was obtained, whose general features are in good agreement with previous assumptions on the receptor structure, but revealed some novel insights since it represents the receptor surface in more detail. Thus, e.g., our model indicates the presence of an H-bond acceptor moiety in the binding site as counterpart to the ligands' cationic ammonium center, rather than a negatively charged carboxylate group. The presented QSAR model is statistically valid and represents the biological data of all tested compounds, including a test set of 21 ligands not used in the modeling process, with very good to excellent accuracy [q(2) (training set, n=66; leave 1/3 out) = 0.84, p(2) (test set, n=21)=0.64]. Moreover, the binding affinities of 13 further spirocyclic sigma(1) ligands were predicted with reasonable accuracy (mean deviation in pK(i) approximately 0.8). Thus, in addition to novel insights into the requirements for binding of spirocyclic piperidines to the sigma(1) receptor, the presented model can be used successfully in the rational design of new sigma(1) ligands. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

Comparative analysis of pharmaceuticals versus industrial chemicals acute aquatic toxicity classification according to the United Nations classification system for chemicals. Assessment of the (Q)SAR predictability of pharmaceuticals acute aquatic toxicity and their predominant acute toxic mode-of-action

DEFF Research Database (Denmark)

Sanderson, Hans; Thomsen, Marianne

2009-01-01

data. Pharmaceuticals were found to be more frequent than industrial chemicals in GHS category III. Acute toxicity was predictable (>92%) using a generic (Q)SAR ((Quantitative) Structure Activity Relationship) suggesting a narcotic MOA. Analysis of model prediction error suggests that 68...... a comprehensive database based on OECD's standardized measured ecotoxicological data and to evaluate if there is generally cause of greater concern with regards to pharmaceutical aquatic toxicological profiles relative to industrial chemicals. Comparisons were based upon aquatic ecotoxicity classification under...... the United Nations Global Harmonized System for classification and labeling of chemicals (GHS). Moreover, we statistically explored whether the predominant mode-of-action (MOA) for pharmaceuticals is narcosis. We found 275 pharmaceuticals with 569 acute aquatic effect data; 23 pharmaceuticals had chronic...

QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors

International Nuclear Information System (INIS)

Kar, Supratik; Roy, Kunal

2010-01-01

One of the major economic alternatives to experimental toxicity testing is the use of quantitative structure-activity relationships (QSARs) which are used in formulating regulatory decisions of environmental protection agencies. In this background, we have modeled a large diverse group of 297 chemicals for their toxicity to Daphnia magna using mechanistically interpretable descriptors. Three-dimensional (3D) (electronic and spatial) and two-dimensional (2D) (topological and information content indices) descriptors along with physicochemical parameter log K o/w (n-octanol/water partition coefficient) and structural descriptors were used as predictor variables. The QSAR models were developed by stepwise multiple linear regression (MLR), partial least squares (PLS), genetic function approximation (GFA), and genetic PLS (G/PLS). All the models were validated internally and externally. Among several models developed using different chemometric tools, the best model based on both internal and external validation characteristics was a PLS equation with 7 descriptors and three latent variables explaining 67.8% leave-one-out predicted variance and 74.1% external predicted variance. The PLS model suggests that higher lipophilicity and electrophilicity, less negative charge surface area and presence of ether linkage, hydrogen bond donor groups and acetylenic carbons are responsible for greater toxicity of chemicals. The developed model may be used for prediction of toxicity, safety and risk assessment of chemicals to achieve better ecotoxicological management and prevent adverse health consequences.

QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors

Energy Technology Data Exchange (ETDEWEB)

Kar, Supratik [Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Raja S C Mullick Road, Kolkata 700032 (India); Roy, Kunal, E-mail: kunalroy_in@yahoo.com [Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Raja S C Mullick Road, Kolkata 700032 (India)

2010-05-15

One of the major economic alternatives to experimental toxicity testing is the use of quantitative structure-activity relationships (QSARs) which are used in formulating regulatory decisions of environmental protection agencies. In this background, we have modeled a large diverse group of 297 chemicals for their toxicity to Daphnia magna using mechanistically interpretable descriptors. Three-dimensional (3D) (electronic and spatial) and two-dimensional (2D) (topological and information content indices) descriptors along with physicochemical parameter log K{sub o/w} (n-octanol/water partition coefficient) and structural descriptors were used as predictor variables. The QSAR models were developed by stepwise multiple linear regression (MLR), partial least squares (PLS), genetic function approximation (GFA), and genetic PLS (G/PLS). All the models were validated internally and externally. Among several models developed using different chemometric tools, the best model based on both internal and external validation characteristics was a PLS equation with 7 descriptors and three latent variables explaining 67.8% leave-one-out predicted variance and 74.1% external predicted variance. The PLS model suggests that higher lipophilicity and electrophilicity, less negative charge surface area and presence of ether linkage, hydrogen bond donor groups and acetylenic carbons are responsible for greater toxicity of chemicals. The developed model may be used for prediction of toxicity, safety and risk assessment of chemicals to achieve better ecotoxicological management and prevent adverse health consequences.

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations.

Science.gov (United States)

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.

The Three Dimensional Quantitative Structure Activity Relationships (3D-QSAR and Docking Studies of Curcumin Derivatives as Androgen Receptor Antagonists

Directory of Open Access Journals (Sweden)

Jing Yang

2012-05-01

Full Text Available Androgen receptor antagonists have been proved to be effective anti-prostate cancer agents. 3D-QSAR and Molecular docking methods were performed on curcumin derivatives as androgen receptor antagonists. The bioactive conformation was explored by docking the potent compound 29 into the binding site of AR. The constructed Comparative Molecular Field Analysis (CoMFA and Comparative Similarity Indices Analysis (CoMSIA models produced statistically significant results with the cross-validated correlation coefficients q² of 0.658 and 0.567, non-cross-validated correlation coefficients r² of 0.988 and 0.978, and predicted correction coefficients r²_pred of 0.715 and 0.793, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of novel potent AR antagonists. A set of 30 new analogs were proposed by utilizing the results revealed in the present study, and were predicted with potential activities in the developed models.

Isolated tear of the tendon to the medial head of gastrocnemius presenting as a painless lump in the calf.

Science.gov (United States)

Watura, Christopher; Harries, William

2009-01-01

We report on a case of isolated tear of the medial head of gastrocnemius tendon. The patient presented with a painless lump in the right calf and denied any prior history of trauma or strain to the leg. A longitudinal split of the tendon was demonstrated at ultrasound and magnetic resonance imaging (MRI). There were no other abnormalities and the gastrocnemius muscle was normal. There are no reports in the literature of isolated gastrocnemius tendon tear. To date the calf muscle complex injury described in this area is tearing of the medial head of gastrocnemius muscle, sometimes referred to as "tennis leg". We conclude that an isolated tear of the tendon to the medial head of gastrocnemius should be considered in the differential diagnosis of a lump or swelling in the upper medial area of the calf and we recommend ultrasound or MRI as the investigations of choice.

In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations

Directory of Open Access Journals (Sweden)

Xiaodong Gao

2016-05-01

Full Text Available Checkpoint kinase 1 (Chk1 is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure–activity relationship (3D-QSAR modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q2 values (0.531, 0.726, fitted correlation r2 coefficients (higher than 0.90, and standard error of prediction (less than 0.250. These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity.

Simulation of nonlinear dynamics of a PWR core by an improved lumped formulation for fuel heat transfer

International Nuclear Information System (INIS)

Su, Jian; Cotta, Renato M.

2000-01-01

In this work, thermohydraulic behaviour of PWR, during reactivity insertion and partial loss-of-flow, is simulated by using a simplified mathematical model of reactor core and primary coolant. An improved lumped parameter formulation for transient heat conduction in fuel rod is used for core heat transfer modelling. Transient temperature response of fuel, cladding and coolant is analysed. (author)

Lumped hydrological models is an Occam' razor for runoff modeling in large Russian Arctic basins

OpenAIRE

Ayzel Georgy

2018-01-01

This study is aimed to investigate the possibility of three lumped hydrological models to predict daily runoff of large-scale Arctic basins for the modern period (1979-2014) in the case of substantial data scarcity. All models were driven only by meteorological forcing reanalysis dataset without any additional information about landscape, soil or vegetation cover properties of studied basins. We found limitations of model parameters calibration in ungauged basins using global optimization alg...

Quantitative structure-activity relationships (QSAR) of 4-amino-2,6-diarylpyrimidine-5-carbonitriles with anti-inflammatory activity

Energy Technology Data Exchange (ETDEWEB)

Silva, Joao Bosco P. da; Ramos, Mozart N.; Barros Neto, Benicio de [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Quimica Fundamental]. E-mail: mramos@ufpe.br; Melo, Sebastiao Jose de [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Antibioticos]. E-mail: melosebastiao@yahoo.com.br; Falcao, Emerson Peter da Silva [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Centro Academico de Vitoria de Santo Antao; Catanho, Maria Teresa J. de Almeida [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Biofisica e Radiobiologia

2008-07-01

The experimental anti-inflammatory activities of eight 4-amino-2,6-diarylpyrimidine-5- carbonitriles were subjected to a QSAR analysis based on results from B3LYP/6-31G(d,p) and AM1 electronic structure calculations. Principal component analyses and regressions based on these data indicate that potentially more active compounds should have low dipole moment and partition coefficient values and also be affected by the values of the charges of the carbon atoms through which the two aromatic rings are bonded to the pyrimidinic ring. Two new molecules were predicted to be at least as active as those with the highest activities used in the model building stage. One of them, having a methoxy group attached to one of the aromatic rings, was predicted to have an anti-inflammatory activity value of 52.3%. This molecule was synthesized and its experimental activity was found to be 52.8%, in agreement with the AM1 theoretical prediction. This value is 5% higher than the largest value used for modeling. (author)

Quantitative structure-activity relationships (QSAR) of 4-amino-2,6-diarylpyrimidine-5-carbonitriles with anti-inflammatory activity

International Nuclear Information System (INIS)

Silva, Joao Bosco P. da; Ramos, Mozart N.; Barros Neto, Benicio de; Melo, Sebastiao Jose de; Falcao, Emerson Peter da Silva; Catanho, Maria Teresa J. de Almeida

2008-01-01

The experimental anti-inflammatory activities of eight 4-amino-2,6-diarylpyrimidine-5- carbonitriles were subjected to a QSAR analysis based on results from B3LYP/6-31G(d,p) and AM1 electronic structure calculations. Principal component analyses and regressions based on these data indicate that potentially more active compounds should have low dipole moment and partition coefficient values and also be affected by the values of the charges of the carbon atoms through which the two aromatic rings are bonded to the pyrimidinic ring. Two new molecules were predicted to be at least as active as those with the highest activities used in the model building stage. One of them, having a methoxy group attached to one of the aromatic rings, was predicted to have an anti-inflammatory activity value of 52.3%. This molecule was synthesized and its experimental activity was found to be 52.8%, in agreement with the AM1 theoretical prediction. This value is 5% higher than the largest value used for modeling. (author)

QSAR study of benzimidazole derivatives inhibition on escherichia coli methionine Aminopeptidase

Directory of Open Access Journals (Sweden)

Zahra Garkani-Nejad

2010-06-01

Full Text Available The paper describes a quantitative structure-activity relationship (QSAR study of IC50 values of benzimidazole derivatives on escherichia coli methionine aminopeptidase. The activity of the 32 inhibitors has been estimated by means of multiple linear regression (MLR and artificial neural network (ANN techniques. The results obtained using the MLR method indicate that the activity of derivatives of benzimidazoles on CoII-loaded escherichia coli methionine aminopeptidase depend on different parameters containing topological descriptors, Burden eigen values, 3D MoRSE descriptors and 2D autocorrelation descriptors. The best artificial neural network model is a fully-connected, feed forward back propagation network with a 5-4-1 architecture. Standard error for the training set using this network was 0.193 with correlation coefficient 0.996 and for the prediction set standard error was 1.41 with correlation coefficient 0.802. Comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive power.

A lumped parameter, low dimension model of heat exchanger

International Nuclear Information System (INIS)

Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami

1980-01-01

This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)

QSAR Study on Caffeine Derivatives Docked on Poly(ARNA Polymerase Protein Cid1

Directory of Open Access Journals (Sweden)

Teodora E. Harsa

2016-06-01

Full Text Available Caffeine is the most commonly ingested alkylxantine and is recognized as a psycho-stimulant. It improves some aspects of cognitive performance, however it reduces the cerebral blood flow both in animals and humans. In this paper a QSAR study on caffeine derivatives, docked on the Poly(ARNA polymerase protein cid1, is reported. A set of forty caffeine derivatives, downloaded from PubChem, was modeled, within the hypermolecule strategy; the predicted activity was LD50 and prediction was done on similarity clusters with the leaders chosen as the best docked ligands on the Poly(ARNA polymerase protein cid1. It was concluded that LD50 of the studied caffeines is not influenced by their binding to the target protein. This work is licensed under a Creative Commons Attribution 4.0 International License.

Mammographic and sonographic findings of steatocystoma multiplex presenting as breast lumps.

Science.gov (United States)

Wan, John Mun Chin; Wong, Jill Su Lin; Tee, Shang-Ian

2012-12-01

Steatocystoma multiplex (SM) is an uncommon cutaneous disorder characterised by multiple intradermal cysts distributed over the trunk and proximal extremities. This condition affects both genders and is often inherited as an autosomal dominant trait, although sporadic cases have been described. This report describes the mammographic and sonographic features of the cysts, which presented as breast lumps, for evaluation. The cysts appeared as numerous well-circumscribed, radiolucent nodules with thin radiodense rims on mammography. On sonography, the cysts could be hypoechoic, isoechoic or demonstrate mixed echoes containing debris-fluid levels, depending on the amount of clear oily liquid and keratinous material. SM can be diagnosed based on a clinical setting of multiple asymptomatic small intradermal nodules over the trunk and proximal extremities, positive family history and imaging findings.

Towards discovering dual functional inhibitors against both wild type and K103N mutant HIV-1 reverse transcriptases: molecular docking and QSAR studies on 4,1-benzoxazepinone analogues

Science.gov (United States)

Zhang, Zhenshan; Zheng, Mingyue; Du, Li; Shen, Jianhua; Luo, Xiaomin; Zhu, Weiliang; Jiang, Hualiang

2006-05-01

To find useful information for discovering dual functional inhibitors against both wild type (WT) and K103N mutant reverse transcriptases (RTs) of HIV-1, molecular docking and 3D-QSAR approaches were applied to a set of twenty-five 4,1-benzoxazepinone analogues of efavirenz (SUSTIVA®), some of them are active against the two RTs. 3D-QSAR models were constructed, based on their binding conformations determined by molecular docking, with r 2 cv values ranging from 0.656 to 0.834 for CoMFA and CoMSIA, respectively. The models were then validated to be highly predictive and extrapolative by inhibitors in two test sets with different molecular skeletons. Furthermore, CoMFA models were found to be well matched with the binding sites of both WT and K103N RTs. Finally, a reasonable pharmacophore model of 4,1-benzoxazepinones were established. The application of the model not only successfully differentiated the experimentally determined inhibitors from non-inhibitors, but also discovered two potent inhibitors from the compound database SPECS. On the basis of both the 3D-QSAR and pharmacophore models, new clues for discovering and designing potent dual functional drug leads against HIV-1 were proposed: (i) adopting positively charged aliphatic group at the cis-substituent of C3; (ii) reducing the electronic density at the position of O4; (iii) positioning a small branched aliphatic group at position of C5; (iv) using the negatively charged bulky substituents at position of C7.

QSAR analysis for nano-sized layered manganese-calcium oxide in water oxidation: An application of chemometric methods in artificial photosynthesis.

Science.gov (United States)

Shahbazy, Mohammad; Kompany-Zareh, Mohsen; Najafpour, Mohammad Mahdi

2015-11-01

Water oxidation is among the most important reactions in artificial photosynthesis, and nano-sized layered manganese-calcium oxides are efficient catalysts toward this reaction. Herein, a quantitative structure-activity relationship (QSAR) model was constructed to predict the catalytic activities of twenty manganese-calcium oxides toward water oxidation using multiple linear regression (MLR) and genetic algorithm (GA) for multivariate calibration and feature selection, respectively. Although there are eight controlled parameters during synthesizing of the desired catalysts including ripening time, temperature, manganese content, calcium content, potassium content, the ratio of calcium:manganese, the average manganese oxidation state and the surface of catalyst, by using GA only three of them (potassium content, the ratio of calcium:manganese and the average manganese oxidation state) were selected as the most effective parameters on catalytic activities of these compounds. The model's accuracy criteria such as R(2)test and Q(2)test in order to predict catalytic rate for external test set experiments; were equal to 0.941 and 0.906, respectively. Therefore, model reveals acceptable capability to anticipate the catalytic activity. Copyright © 2015 Elsevier B.V. All rights reserved.

QSAR studies for the acute toxicity of nitrobenzenes to the Tetrahymena pyriformis

Directory of Open Access Journals (Sweden)

Wang Dan-Dan

2014-01-01

Full Text Available Quantitative structure-activity relationship (QSAR models play a key role in finding the relationship between molecular structures and the toxicity of nitrobenzenes to Tetrahymena pyriformis. In this work, genetic algorithm, along with partial least square (GA-PLS was employed to select optimal subset of descriptors that have significant contribution to the toxicity of nitrobenzenes to Tetrahymena pyriformis. A set of five descriptors, namely G2, HOMT, G(Cl…Cl, Mor03v and MAXDP, was used for the prediction of the toxicity of 45 nitrobenzene derivatives and then were used to build the model by multiple linear regression (MLR method. It turned out that the built model, whose stability was confirmed using the leave-one-out validation and external validation test, showed high statistical significance (R2=0.963, Q2LOO=0.944. Moreover, Y-scrambling test indicated there was no chance correlation in this model.

QSAR development and profiling of 72,524 REACH substances for PXR activation and CYP3A4 induction

DEFF Research Database (Denmark)

Abildgaard Rosenberg, Sine; Xia, M.; Huang, R.

2017-01-01

,524 substances pre-registered under the EU chemicals regulation, REACH, and the models could predict 52.5% to 71.9% of the substances within their respective applicability domains. These predictions can, for example, be used for priority setting and in weight-of-evidence assessments of chemicals. Statistical...... analyses of the experimental drug dataset and the QSAR-predicted set of REACH substances were performed to identify similarities and differences in frequencies of overlapping positive results for PXR binding, PXR activation and CYP3A4 induction between the two datasets....

A passive terahertz video camera based on lumped element kinetic inductance detectors

Energy Technology Data Exchange (ETDEWEB)

Rowe, Sam, E-mail: sam.rowe@astro.cf.ac.uk; Pascale, Enzo; Doyle, Simon; Dunscombe, Chris; Hargrave, Peter; Papageorgio, Andreas; Ade, Peter A. R.; Barry, Peter; Bideaud, Aurélien; Brien, Tom; Dodd, Chris; House, Julian; Moseley, Paul; Sudiwala, Rashmi; Tucker, Carole; Walker, Ian [Astronomy Instrumentation Group, School of Physics and Astronomy, Cardiff University, Cardiff CF24 3AA (United Kingdom); Wood, Ken [QMC Instruments Ltd., School of Physics and Astronomy, Cardiff University, Cardiff CF24 3AA (United Kingdom); Grainger, William [Rutherford Appleton Laboratory, STFC, Swindon SN2 1SZ (United Kingdom); Mauskopf, Philip [Astronomy Instrumentation Group, School of Physics and Astronomy, Cardiff University, Cardiff CF24 3AA (United Kingdom); School of Earth Science and Space Exploration, Arizona State University, Tempe, Arizona 85281 (United States); Spencer, Locke [Department of Physics and Astronomy, University of Lethbridge, Lethbridge, Alberta T1K 3M4 (Canada)

2016-03-15

We have developed a passive 350 GHz (850 μm) video-camera to demonstrate lumped element kinetic inductance detectors (LEKIDs)—designed originally for far-infrared astronomy—as an option for general purpose terrestrial terahertz imaging applications. The camera currently operates at a quasi-video frame rate of 2 Hz with a noise equivalent temperature difference per frame of ∼0.1 K, which is close to the background limit. The 152 element superconducting LEKID array is fabricated from a simple 40 nm aluminum film on a silicon dielectric substrate and is read out through a single microwave feedline with a cryogenic low noise amplifier and room temperature frequency domain multiplexing electronics.

A passive terahertz video camera based on lumped element kinetic inductance detectors

International Nuclear Information System (INIS)

Rowe, Sam; Pascale, Enzo; Doyle, Simon; Dunscombe, Chris; Hargrave, Peter; Papageorgio, Andreas; Ade, Peter A. R.; Barry, Peter; Bideaud, Aurélien; Brien, Tom; Dodd, Chris; House, Julian; Moseley, Paul; Sudiwala, Rashmi; Tucker, Carole; Walker, Ian; Wood, Ken; Grainger, William; Mauskopf, Philip; Spencer, Locke

2016-01-01

We have developed a passive 350 GHz (850 μm) video-camera to demonstrate lumped element kinetic inductance detectors (LEKIDs)—designed originally for far-infrared astronomy—as an option for general purpose terrestrial terahertz imaging applications. The camera currently operates at a quasi-video frame rate of 2 Hz with a noise equivalent temperature difference per frame of ∼0.1 K, which is close to the background limit. The 152 element superconducting LEKID array is fabricated from a simple 40 nm aluminum film on a silicon dielectric substrate and is read out through a single microwave feedline with a cryogenic low noise amplifier and room temperature frequency domain multiplexing electronics.

QSAR study of HCV NS5B polymerase inhibitors using the genetic algorithm-multiple linear regression (GA-MLR).

Science.gov (United States)

Rafiei, Hamid; Khanzadeh, Marziyeh; Mozaffari, Shahla; Bostanifar, Mohammad Hassan; Avval, Zhila Mohajeri; Aalizadeh, Reza; Pourbasheer, Eslam

2016-01-01

Quantitative structure-activity relationship (QSAR) study has been employed for predicting the inhibitory activities of the Hepatitis C virus (HCV) NS5B polymerase inhibitors . A data set consisted of 72 compounds was selected, and then different types of molecular descriptors were calculated. The whole data set was split into a training set (80 % of the dataset) and a test set (20 % of the dataset) using principle component analysis. The stepwise (SW) and the genetic algorithm (GA) techniques were used as variable selection tools. Multiple linear regression method was then used to linearly correlate the selected descriptors with inhibitory activities. Several validation technique including leave-one-out and leave-group-out cross-validation, Y-randomization method were used to evaluate the internal capability of the derived models. The external prediction ability of the derived models was further analyzed using modified r(2), concordance correlation coefficient values and Golbraikh and Tropsha acceptable model criteria's. Based on the derived results (GA-MLR), some new insights toward molecular structural requirements for obtaining better inhibitory activity were obtained.

Modifying tetramethyl–nitrophenyl–imidazoline with amino acids: design, synthesis, and 3D-QSAR for improving inflammatory pain therapy

Directory of Open Access Journals (Sweden)

Jiang X

2015-04-01

Full Text Available Xueyun Jiang,1 Yuji Wang,1 Haimei Zhu,1 Yaonan Wang,1 Ming Zhao,1,2 Shurui Zhao,1 Jianhui Wu,1 Shan Li,1 Shiqi Peng11Beijing Area Major Laboratory of Peptide and Small Molecular Drugs, Engineering Research Center of Endogenous Prophylactic of Ministry of Education of China, Beijing Laboratory of Biomedical Materials, College of Pharmaceutical Sciences, Capital Medical University, Beijing, People’s Republic of China; 2Faculty of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, TaiwanAbstract: With the help of pharmacophore analysis and docking investigation, 15 novel 1-(4,4,5,5-tetramethyl-2-(3-nitrophenyl-4,5-dihydroimidazol-1-yl-oxyacetyl-L-amino acids (6a–o were designed, synthesized, and assayed. On tail-flick and xylene-induced ear edema models, 10 µmol/kg 6a–o exhibited excellent oral anti-inflammation and analgesic activity. The dose-dependent assay of their representative 6f indicates that the effective dose should be 3.3 µmol/kg. The correlation of the three-dimensional quantitative structure–activity relationship with the docking analysis provides a basis for the rational design of drugs to treat inflammatory pain.Keywords: tetramethylimidazoline, analgesic, anti-inflammatory, 3D-QSAR

On the time-stepping stability of continuous mass-lumped and discontinuous Galerkin finite elements for the 3D acoustic wave equation

NARCIS (Netherlands)

Zhebel, E.; Minisini, S.; Mulder, W.A.

2012-01-01

We solve the three-dimensional acoustic wave equation, discretized on tetrahedral meshes. Two methods are considered: mass-lumped continuous finite elements and the symmetric interior-penalty discontinuous Galerkin method (SIP-DG). Combining the spatial discretization with the leap-frog

Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response

Science.gov (United States)

Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.

2016-06-01

Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.

On the treatment of plane fusion front in lumped parameter thermal models with convection

International Nuclear Information System (INIS)

Le Tellier, R.; Skrzypek, E.; Saas, L.

2017-01-01

Highlights: • Solid phase approximations for a two-phase Stefan fusion problem with convection are analyzed. • A reference solution combines integral conservation eqs and a FE solution of the 1D heat equation. • Numerical results are presented for a transient in light water reactor severe accident analysis. • The models performances are highlighted on fusion transients in terms of Biot and Stefan numbers. - Abstract: Within the framework of lumped parameter models for integral codes, this paper focuses on the modeling of a two-phase Stefan fusion problem with natural convection in the liquid phase. In particular, this specific Stefan problem is of interest when studying corium pool behavior in the framework of light water reactor severe accident analysis. The objective of this research is to analyze the applicability of different approximations related to the modeling of the solid phase in terms of boundary heat flux closure relations. Three different approximations are considered: a quadratic profile based model, a model where a parameter controls the power partitioning at the interface and the steady state conduction assumption. These models are compared with an accurate front-tracking solution of this plane fusion front problem. This “reference” is obtained by combining the same integral conservation equations as the approximate models with a mesh-based solution of the 1D heat equation. Numerical results are discussed for a typical configuration of interest for corium pool analysis. Different fusion transients (constructed from nondimensionalization considerations in terms of Biot and Stefan numbers) are used in order to highlight the potential and limitations of the different approximations.

A new analytical method for estimating lumped parameter constants of linear viscoelastic models from strain rate tests

Science.gov (United States)

Mattei, G.; Ahluwalia, A.

2018-04-01

We introduce a new function, the apparent elastic modulus strain-rate spectrum, E_{app} ( \\dot{ɛ} ), for the derivation of lumped parameter constants for Generalized Maxwell (GM) linear viscoelastic models from stress-strain data obtained at various compressive strain rates ( \\dot{ɛ}). The E_{app} ( \\dot{ɛ} ) function was derived using the tangent modulus function obtained from the GM model stress-strain response to a constant \\dot{ɛ} input. Material viscoelastic parameters can be rapidly derived by fitting experimental E_{app} data obtained at different strain rates to the E_{app} ( \\dot{ɛ} ) function. This single-curve fitting returns similar viscoelastic constants as the original epsilon dot method based on a multi-curve global fitting procedure with shared parameters. Its low computational cost permits quick and robust identification of viscoelastic constants even when a large number of strain rates or replicates per strain rate are considered. This method is particularly suited for the analysis of bulk compression and nano-indentation data of soft (bio)materials.

Probing the Hypothesis of SAR Continuity Restoration by the Removal of Activity Cliffs Generators in QSAR.

Science.gov (United States)

Cruz-Monteagudo, Maykel; Medina-Franco, José L; Perera-Sardiña, Yunier; Borges, Fernanda; Tejera, Eduardo; Paz-Y-Miño, Cesar; Pérez-Castillo, Yunierkis; Sánchez-Rodríguez, Aminael; Contreras-Posada, Zuleidys; Cordeiro, M Natália D S

2016-01-01

In this work we report the first attempt to study the effect of activity cliffs over the generalization ability of machine learning (ML) based QSAR classifiers, using as study case a previously reported diverse and noisy dataset focused on drug induced liver injury (DILI) and more than 40 ML classification algorithms. Here, the hypothesis of structure-activity relationship (SAR) continuity restoration by activity cliffs removal is tested as a potential solution to overcome such limitation. Previously, a parallelism was established between activity cliffs generators (ACGs) and instances that should be misclassified (ISMs), a related concept from the field of machine learning. Based on this concept we comparatively studied the classification performance of multiple machine learning classifiers as well as the consensus classifier derived from predictive classifiers obtained from training sets including or excluding ACGs. The influence of the removal of ACGs from the training set over the virtual screening performance was also studied for the respective consensus classifiers algorithms. In general terms, the removal of the ACGs from the training process slightly decreased the overall accuracy of the ML classifiers and multi-classifiers, improving their sensitivity (the weakest feature of ML classifiers trained with ACGs) but decreasing their specificity. Although these results do not support a positive effect of the removal of ACGs over the classification performance of ML classifiers, the "balancing effect" of ACG removal demonstrated to positively influence the virtual screening performance of multi-classifiers based on valid base ML classifiers. Specially, the early recognition ability was significantly favored after ACGs removal. The results presented and discussed in this work represent the first step towards the application of a remedial solution to the activity cliffs problem in QSAR studies.

Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity.

Science.gov (United States)

Barigye, Stephen J; Freitas, Matheus P; Ausina, Priscila; Zancan, Patricia; Sola-Penna, Mauro; Castillo-Garit, Juan A

2018-02-12

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and aromatase inhibitory activities. The obtained results suggest that the 2D-DFT MIA-QSAR method may be useful in ligand-based virtual screening of new molecular entities of therapeutic utility.

Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF)

Energy Technology Data Exchange (ETDEWEB)

Gissi, Andrea [Laboratory of Environmental Chemistry and Toxicology, IRCCS – Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano (Italy); Dipartimento di Farmacia – Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Via E. Orabona 4, 70125 Bari (Italy); Lombardo, Anna; Roncaglioni, Alessandra [Laboratory of Environmental Chemistry and Toxicology, IRCCS – Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano (Italy); Gadaleta, Domenico [Laboratory of Environmental Chemistry and Toxicology, IRCCS – Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano (Italy); Dipartimento di Farmacia – Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Via E. Orabona 4, 70125 Bari (Italy); Mangiatordi, Giuseppe Felice; Nicolotti, Orazio [Dipartimento di Farmacia – Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Via E. Orabona 4, 70125 Bari (Italy); Benfenati, Emilio, E-mail: emilio.benfenati@marionegri.it [Laboratory of Environmental Chemistry and Toxicology, IRCCS – Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano (Italy)

2015-02-15

The bioconcentration factor (BCF) is an important bioaccumulation hazard assessment metric in many regulatory contexts. Its assessment is required by the REACH regulation (Registration, Evaluation, Authorization and Restriction of Chemicals) and by CLP (Classification, Labeling and Packaging). We challenged nine well-known and widely used BCF QSAR models against 851 compounds stored in an ad-hoc created database. The goodness of the regression analysis was assessed by considering the determination coefficient (R{sup 2}) and the Root Mean Square Error (RMSE); Cooper's statistics and Matthew's Correlation Coefficient (MCC) were calculated for all the thresholds relevant for regulatory purposes (i.e. 100 L/kg for Chemical Safety Assessment; 500 L/kg for Classification and Labeling; 2000 and 5000 L/kg for Persistent, Bioaccumulative and Toxic (PBT) and very Persistent, very Bioaccumulative (vPvB) assessment) to assess the classification, with particular attention to the models' ability to control the occurrence of false negatives. As a first step, statistical analysis was performed for the predictions of the entire dataset; R{sup 2}>0.70 was obtained using CORAL, T.E.S.T. and EPISuite Arnot–Gobas models. As classifiers, ACD and log P-based equations were the best in terms of sensitivity, ranging from 0.75 to 0.94. External compound predictions were carried out for the models that had their own training sets. CORAL model returned the best performance (R{sup 2}{sub ext}=0.59), followed by the EPISuite Meylan model (R{sup 2}{sub ext}=0.58). The latter gave also the highest sensitivity on external compounds with values from 0.55 to 0.85, depending on the thresholds. Statistics were also compiled for compounds falling into the models Applicability Domain (AD), giving better performances. In this respect, VEGA CAESAR was the best model in terms of regression (R{sup 2}=0.94) and classification (average sensitivity>0.80). This model also showed the best

Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF)

International Nuclear Information System (INIS)

Gissi, Andrea; Lombardo, Anna; Roncaglioni, Alessandra; Gadaleta, Domenico; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio; Benfenati, Emilio

2015-01-01

The bioconcentration factor (BCF) is an important bioaccumulation hazard assessment metric in many regulatory contexts. Its assessment is required by the REACH regulation (Registration, Evaluation, Authorization and Restriction of Chemicals) and by CLP (Classification, Labeling and Packaging). We challenged nine well-known and widely used BCF QSAR models against 851 compounds stored in an ad-hoc created database. The goodness of the regression analysis was assessed by considering the determination coefficient (R 2 ) and the Root Mean Square Error (RMSE); Cooper's statistics and Matthew's Correlation Coefficient (MCC) were calculated for all the thresholds relevant for regulatory purposes (i.e. 100 L/kg for Chemical Safety Assessment; 500 L/kg for Classification and Labeling; 2000 and 5000 L/kg for Persistent, Bioaccumulative and Toxic (PBT) and very Persistent, very Bioaccumulative (vPvB) assessment) to assess the classification, with particular attention to the models' ability to control the occurrence of false negatives. As a first step, statistical analysis was performed for the predictions of the entire dataset; R 2 >0.70 was obtained using CORAL, T.E.S.T. and EPISuite Arnot–Gobas models. As classifiers, ACD and log P-based equations were the best in terms of sensitivity, ranging from 0.75 to 0.94. External compound predictions were carried out for the models that had their own training sets. CORAL model returned the best performance (R 2 ext =0.59), followed by the EPISuite Meylan model (R 2 ext =0.58). The latter gave also the highest sensitivity on external compounds with values from 0.55 to 0.85, depending on the thresholds. Statistics were also compiled for compounds falling into the models Applicability Domain (AD), giving better performances. In this respect, VEGA CAESAR was the best model in terms of regression (R 2 =0.94) and classification (average sensitivity>0.80). This model also showed the best regression (R 2 =0.85) and

Analysis of groundwater discharge with a lumped-parameter model, using a case study from Tajikistan

Science.gov (United States)

Pozdniakov, S. P.; Shestakov, V. M.

A lumped-parameter model of groundwater balance is proposed that permits an estimate of discharge variability in comparison with the variability of recharge, by taking into account the influence of aquifer parameters. Recharge-discharge relationships are analysed with the model for cases of deterministic and stochastic recharge time-series variations. The model is applied to study the temporal variability of groundwater discharge in a river valley in the territory of Tajikistan, an independent republic in Central Asia. Résumé Un modèle global de bilan d'eau souterraine a été développé pour estimer la variabilité de l'écoulement par rapport à celle de la recharge, en prenant en compte l'influence des paramètres de l'aquifère. Les relations entre recharge et écoulement sont analysées à l'aide du modèle pour des variations des chroniques de recharge soit déterministes, soit stochastiques. Le modèle est appliquéà l'étude de la variabilité temporelle de l'écoulement souterrain vers une rivière, dans le Tadjikistan, une république indépendante d'Asie centrale. Resumen Se propone un modelo de parámetros concentrados para realizar el balance de aguas subterráneas, el cual permite estimar la variabilidad en la descarga con respecto a la variabilidad en la recarga, en función de los parámetros que caracterizan el acuífero. Las relaciones entre recarga y descarga se analizan con el modelo para distintos casos de series temporales de recarga, tanto deterministas como estocásticas. El modelo se aplica al estudio de la variabilidad temporal de la descarga en un valle aluvial de Tadyikistán, una república independiente del Asia Central.

Frequency Combs in a Lumped-Element Josephson-Junction Circuit

Science.gov (United States)

Khan, Saeed; Türeci, Hakan E.

2018-04-01

We investigate the dynamics of a microwave-driven Josephson junction capacitively coupled to a lumped-element L C oscillator. In the regime of driving where the Josephson junction can be approximated as a Kerr oscillator, this minimal nonlinear system has been previously shown to exhibit a bistability in phase and amplitude. In the present study, we characterize the full phase diagram and show that besides a parameter regime exhibiting bistability, there is also a regime of self-oscillations characterized by a frequency comb in its spectrum. We discuss the mechanism of comb generation which appears to be different from those studied in microcavity frequency combs and mode-locked lasers. We then address the fate of the comblike spectrum in the regime of strong quantum fluctuations, reached when nonlinearity becomes the dominant scale with respect to dissipation. We find that the nonlinearity responsible for the emergence of the frequency combs also leads to its dephasing, leading to broadening and ultimate disappearance of sharp spectral peaks. Our study explores the fundamental question of the impact of quantum fluctuations for quantum systems which do not possess a stable fixed point in the classical limit.

Finding and testing network communities by lumped Markov chains.

Science.gov (United States)

Piccardi, Carlo

2011-01-01

Identifying communities (or clusters), namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called "persistence probability" is associated to a cluster, which is then defined as an "α-community" if such a probability is not smaller than α. Consistently, a partition composed of α-communities is an "α-partition." These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired α-level allows one to immediately select the α-partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.

Finding and testing network communities by lumped Markov chains.

Directory of Open Access Journals (Sweden)

Carlo Piccardi

Full Text Available Identifying communities (or clusters, namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called "persistence probability" is associated to a cluster, which is then defined as an "α-community" if such a probability is not smaller than α. Consistently, a partition composed of α-communities is an "α-partition." These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired α-level allows one to immediately select the α-partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.

Towards a lumped reaction model for future designer fuels

Energy Technology Data Exchange (ETDEWEB)

Vandersickel, A.; Wright, Y.M.; Boulouchos, K. [ETH Zurich, Aerothermochemistry and Combustion Systems Laboratory, Zurich (Switzerland). Inst. of Energy Technology

2009-07-01

The homogeneous charge compression ignition (HCCI) is one of the most promising engine processes to simultaneously reduce nitrogen oxide and soot emissions. However, its applicability is hindered by its relatively limited operating range. Designer fuels offer unique possibilities for tailoring evaporation and auto-ignition properties, offering a means to control and expand the HCCI operation range. The identification of HCCI relevant fuel properties as well as the definition of a new fuel index able to describe a fuels suitability for HCCI was required in order to develop such designer fuels. This paper discussed a numerical and experimental investigation of a large set of technical fuels covering a wide range of properties. The paper discussed mechanism development approaches, optimization of the lumped mechanism, and and results. Zheng's 7-step reaction mechanism was successfully coupled with a genetic optimization algorithm and fitted to n-heptane ignition delay data. It was concluded that the presented coupled approach could improve the predictive quality of the model and demonstrate that the Zheng model was sufficiently elaborate to emulate the influence of temperature, pressure, exhaust gas recirculation and lambda on ignition. 8 refs., 1 tab., 3 figs.