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Sample records for qsar analysis methods

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

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    Fang, Cheng; Xiao, Zhiyan

    2016-01-01

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

  2. QSAR Methods to Screen Endocrine Disruptors

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    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.

  3. Sparse QSAR modelling methods for therapeutic and regenerative medicine

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    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.

  4. 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.

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

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    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.

  6. QUANTITAVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS (QSAR OF ANTIMALARIAL 1,10-PHENANTHROLINE DERIVATIVES COMPOUNDS

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    Ruslin Hadanu

    2010-06-01

    Full Text Available Quantitative Electronic Structure-Activity Relationship (QSAR analysis of a series of 1,10-phenanthroline derivatives as antiplasmodial compounds have been conducted using atomic net charges (q, dipole moment (μ ELUMO, EHOMO, polarizability (α and log P as the descriptors. The descriptors were obtained from computational chemistry method using semi-empirical PM3. Antiplasmodial activities were taken as the activity of the drugs  against  chloroquine-resistant Plasmodium falciparum FCR3 strain and are presented as the value of ln (1/IC50 where IC50 is an effective concentration inhibiting 50% of the parasite growth. The best model of QSAR model was determine by multiple linear regression method and giving equation of QSAR: ln 1/IC50  =  3.732 + (5.098 qC5 + (7.051 qC7 + (36.696 qC9 + (41.467 qC11 -(135.497 qC12 + (0.332 μ -                    (0.170 α + (0.757 log P. The equation was significant on the 95% level with statistical parameters: n=16; r=0.987; r2= 0.975; SE=0.317;  Fcalc/Ftable = 15.337 and gave the PRESS=0.707. Its means that there were only a relatively few deviations between the experimental and theoretical data of antimalarial activity.   Keywords: QSAR, antimalarial, semi-empirical method, 1,10-phenanthroline.

  7. QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

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    Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

    2009-01-01

    A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

  8. QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP ANALYSIS (QSAR OF VINCADIFFORMINE ANALOGUES AS THE ANTIPLASMODIAL COMPOUNDS OF THE CHLOROQUINOSENSIBLE STRAIN

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    Iqmal Tahir

    2010-06-01

    Full Text Available Quantitative Structure-Activity Relationship (QSAR analysis of vincadifformine analogs as an antimalarial drug has been conducted using atomic net charges (q, moment dipole (, LUMO (Lowest Unoccupied Molecular Orbital and HOMO (Highest Occupied Molecular Orbital energies, molecular mass (m as well as surface area (A as the predictors to their activity. Data of predictors are obtained from computational chemistry method using semi-empirical molecular orbital AM1 calculation. Antimalarial activities were taken as the activity of the drugs against chloroquine-sensitive Plasmodium falciparum (Nigerian Cell strain and were presented as the value of ln(1/IC50 where IC50 is an effective concentration inhibiting 50% of the parasite growth. The best QSAR model has been determined by multiple linier regression analysis giving QSAR equation: Log (1/IC50 = 9.602.qC1 -17.012.qC2 +6.084.qC3 -19.758.qC5 -6.517.qC6 +2.746.qC7 -6.795.qN +6.59.qC8 -0.190. -0.974.ELUMO +0.515.EHOMO -0.274. +0.029.A -1.673 (n = 16; r = 0.995; SD = 0.099; F = 2.682   Keywords: QSAR analysis, antimalaria, vincadifformine.

  9. QSAR analysis for nano-sized layered manganese-calcium oxide in water oxidation: An application of chemometric methods in artificial photosynthesis.

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    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.

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

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    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.

  11. 3D-QSAR Investigation of Synthetic Antioxidant Chromone Derivatives by Molecular Field Analysis

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    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.

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

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    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.

  13. 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.

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

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    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.

  15. QSAR Studies on Andrographolide Derivatives as α-Glucosidase Inhibitors

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    Shaohui Cai

    2010-03-01

    Full Text Available Andrographolide derivatives were shown to inhibit α-glucosidase. To investigate the relationship between activities and structures of andrographolide derivatives, a training set was chosen from 25 andrographolide derivatives by the principal component analysis (PCA method, and a quantitative structure-activity relationship (QSAR was established by 2D and 3D QSAR methods. The cross-validation r2 (0.731 and standard error (0.225 illustrated that the 2D-QSAR model was able to identify the important molecular fragments and the cross-validation r2 (0.794 and standard error (0.127 demonstrated that the 3D-QSAR model was capable of exploring the spatial distribution of important fragments. The obtained results suggested that proposed combination of 2D and 3D QSAR models could be useful in predicting the α-glucosidase inhibiting activity of andrographolide derivatives.

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

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    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.

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

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    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

  18. Current Mathematical Methods Used in QSAR/QSPR Studies

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    Peixun Liu

    2009-04-01

    Full Text Available This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP, Project Pursuit Regression (PPR and Local Lazy Regression (LLR have appeared on the QASR/QSPR stage. At the same time, the earlier methods, including Multiple Linear Regression (MLR, Partial Least Squares (PLS, Neural Networks (NN, Support Vector Machine (SVM and so on, are being upgraded to improve their performance in QASR/QSPR studies. These new and upgraded methods and algorithms are described in detail, and their advantages and disadvantages are evaluated and discussed, to show their application potential in QASR/QSPR studies in the future.

  19. Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

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    Al-Masri, Ihab M; Mohammad, Mohammad K; Taha, Mutasem O

    2008-11-01

    Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

  20. Evaluation on joint toxicity of chlorinated anilines and cadmium to Photobacterium phosphoreum and QSAR analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Hao, E-mail: realking163@163.com [School of Life and Chemistry, Jiangsu Second Normal University, Nanjing, Jiangsu 210013 (China); Wang, Chao; Shi, Jiaqi [State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Nanjing, Jiangsu 210023 (China); Chen, Lei [School of Life and Chemistry, Jiangsu Second Normal University, Nanjing, Jiangsu 210013 (China)

    2014-08-30

    Highlights: • Cd has different effects on joint toxicity when in different concentrations. • The toxicity of most binary mixtures decreases when Cd concentration rises. • Different QSAR models are developed to predict the joint toxicity. • Descriptors in QSARs can help to elucidate the joint toxicity mechanism. • Van der Waals’ force or complexation may reduce the toxicity of mixtures. - Abstract: The individual IC{sub 50} (the concentrations causing a 50% inhibition of bioluminescence after 15 min exposure) of cadmium ion (Cd) and nine chlorinated anilines to Photobacterium phosphoreum (P. phosphoreum) were determined. In order to evaluate the combined effects of the nine chlorinated anilines and Cd, the toxicities of chlorinated anilines combined with different concentrations of Cd were determined, respectively. The results showed that the number of chlorinated anilines manifesting synergy with Cd decreased with the increasing Cd concentration, and the number manifesting antagonism decreased firstly and then increased. The joint toxicity of mixtures at low Cd concentration was weaker than that of most binary mixtures when combined with Cd at medium and high concentrations as indicated by TU{sub Total}. QSAR analysis showed that the single toxicity of chlorinated anilines was related to the energy of the lowest unoccupied molecular orbital (E{sub LUMO}). When combined with different concentrations of Cd, the toxicity was related to the energy difference (E{sub HOMO} − E{sub LUMO}) with different coefficients. Van der Waals’ force or the complexation between chlorinated anilines and Cd had an impact on the toxicity of combined systems, which could account for QSAR models with different physico-chemical descriptors.

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

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    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

  2. QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

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    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.

  3. Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

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    Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

    2015-03-01

    Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

  4. QSAR modeling and chemical space analysis of antimalarial compounds

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    Sidorov, Pavel; Viira, Birgit; Davioud-Charvet, Elisabeth; Maran, Uko; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

    2017-05-01

    Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including 3000 molecules tested in one or several of 17 anti- Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

  5. Advances in the replacement and enhanced replacement method in QSAR and QSPR theories.

    Science.gov (United States)

    Mercader, Andrew G; Duchowicz, Pablo R; Fernández, Francisco M; Castro, Eduardo A

    2011-07-25

    The selection of an optimal set of molecular descriptors from a much greater pool of such regression variables is a crucial step in the development of QSAR and QSPR models. The aim of this work is to further improve this important selection process. For this reason three different alternatives for the initial steps of our recently developed enhanced replacement method (ERM) and replacement method (RM) are proposed. These approaches had previously proven to yield near optimal results with a much smaller number of linear regressions than the full search. The algorithms were tested on four different experimental data sets, formed by collections of 116, 200, 78, and 100 experimental records from different compounds and 1268, 1338, 1187, and 1306 molecular descriptors, respectively. The comparisons showed that one of the new alternatives further improves the ERM, which has shown to be superior to genetic algorithms for the selection of an optimal set of molecular descriptors from a much greater pool. The new proposed alternative also improves the simpler and the lower computational demand algorithm RM.

  6. 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.

  7. 4D-Qsar Study of Some Pyrazole Pyridine Carboxylic Acid Derivatives by Electron Conformational-Genetic Algorithm Method.

    Science.gov (United States)

    Tuzun, Burak; Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin

    2018-05-13

    In the present work, pharmacophore identification and biological activity prediction for 86 pyrazole pyridine carboxylic acid derivatives were made using the electron conformational genetic algorithm approach which was introduced as a 4D-QSAR analysis by us in recent years. In the light of the data obtained from quantum chemical calculations at HF/6-311 G** level, the electron conformational matrices of congruity (ECMC) were constructed by EMRE software. Comparing the matrices, electron conformational submatrix of activity (ECSA, Pha) was revealed that are common for these compounds within a minimum tolerance. A parameter pool was generated considering the obtained pharmacophore. To determine the theoretical biological activity of molecules and identify the best subset of variables affecting bioactivities, we used the nonlinear least square regression method and genetic algorithm. The results obtained in this study are in good agreement with the experimental data presented in the literature. The model for training and test sets attained by the optimum 12 parameters gave highly satisfactory results with R2training= 0.889, q2=0.839 and SEtraining=0.066, q2ext1 = 0.770, q2ext2 = 0.750, q2ext3=0.824, ccctr = 0.941, ccctest = 0.869 and cccall = 0.927. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  8. 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.

  9. QSAR analysis of salicylamide isosteres with the use of quantum chemical molecular descriptors.

    Science.gov (United States)

    Dolezal, R; Van Damme, S; Bultinck, P; Waisser, K

    2009-02-01

    Quantitative relationships between the molecular structure and the biological activity of 49 isosteric salicylamide derivatives as potential antituberculotics with a new mechanism of action against three Mycobacterial strains were investigated. The molecular structures were represented by quantum chemical B3LYP/6-31G( *) based molecular descriptors. A resulting set of 220 molecular descriptors, including especially electronic properties, was statistically analyzed using multiple linear regression, resulting in acceptable and robust QSAR models. The best QSAR model was found for Mycobacterium tuberculosis (r(2)=0.92; q(2)=0.89), and somewhat less good QSAR models were found for Mycobacterium avium (r(2)=0.84; q(2)=0.78) and Mycobacterium kansasii (r(2)=0.80; q(2)=0.56). All QSAR models were cross-validated using the leave-10-out procedure.

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

    International Nuclear Information System (INIS)

    Jagiello, Karolina; Grzonkowska, Monika; Swirog, Marta; Ahmed, Lucky; Rasulev, Bakhtiyor; Avramopoulos, Aggelos; Papadopoulos, Manthos G.; Leszczynski, Jerzy; Puzyn, Tomasz

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Jagiello, Karolina; Grzonkowska, Monika; Swirog, Marta [University of Gdansk, Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection (Poland); Ahmed, Lucky; Rasulev, Bakhtiyor [Jackson State University, Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry (United States); Avramopoulos, Aggelos; Papadopoulos, Manthos G. [National Hellenic Research Foundation, Institute of Biology, Pharmaceutical Chemistry and Biotechnology (Greece); Leszczynski, Jerzy [Jackson State University, Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry (United States); Puzyn, Tomasz, E-mail: t.puzyn@qsar.eu.org [University of Gdansk, Laboratory of Environmental Chemometrics, Faculty of Chemistry, Institute for Environmental and Human Health Protection (Poland)

    2016-09-15

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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. INTEGRATION OF QSAR AND SAR METHODS FOR THE MECHANISTIC INTERPRETATION OF PREDICTIVE MODELS FOR CARCINOGENICITY

    Directory of Open Access Journals (Sweden)

    Natalja Fjodorova

    2012-07-01

    Full Text Available The knowledge-based Toxtree expert system (SAR approach was integrated with the statistically based counter propagation artificial neural network (CP ANN model (QSAR approach to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.

  19. 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.

  20. 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

  1. a QSAR Study

    African Journals Online (AJOL)

    DK

    Une étude Relation Quantitative Structure- Activité (QSAR) a été réalisée pour évaluer la toxicité relative d'un mélange composé de ... of a substance to enter cells through the lipid ..... evaluations of regression based and classification QSARs,.

  2. 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%.

  3. 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%.

  4. 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

  5. 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).

  6. Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational- Genetic Algorithm Method.

    Science.gov (United States)

    Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin

    2018-01-01

    The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R2 training= 0.817, q 2=0.718 and SEtraining=0.066, q2 ext1 = 0.867, q2 ext2 = 0.849, q2 ext3 =0.895, ccctr = 0.895, ccctest = 0.930 and cccall = 0.905. Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  7. Building up a QSAR model for toxicity toward Tetrahymena pyriformis by the Monte Carlo method: A case of benzene derivatives.

    Science.gov (United States)

    Toropova, Alla P; Schultz, Terry W; Toropov, Andrey A

    2016-03-01

    Data on toxicity toward Tetrahymena pyriformis is indicator of applicability of a substance in ecologic and pharmaceutical aspects. Quantitative structure-activity relationships (QSARs) between the molecular structure of benzene derivatives and toxicity toward T. pyriformis (expressed as the negative logarithms of the population growth inhibition dose, mmol/L) are established. The available data were randomly distributed three times into the visible training and calibration sets, and invisible validation sets. The statistical characteristics for the validation set are the following: r(2)=0.8179 and s=0.338 (first distribution); r(2)=0.8682 and s=0.341 (second distribution); r(2)=0.8435 and s=0.323 (third distribution). These models are built up using only information on the molecular structure: no data on physicochemical parameters, 3D features of the molecular structure and quantum mechanics descriptors are involved in the modeling process. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. 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

  9. 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....

  10. 3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA.

    Science.gov (United States)

    Pourbasheer, Eslam; Aalizadeh, Reza; Ebadi, Amin; Ganjali, Mohammad Reza

    2015-01-01

    Three-dimensional quantitative structure-activity relationship was developed for the series of compounds as malonyl-CoA decarboxylase antagonists (MCD) using the CoMFA and CoMSIA methods. The statistical parameters for CoMFA (q(2)=0.558, r(2)=0.841) and CoMSIA (q(2)= 0.615, r(2) = 0.870) models were derived based on 38 compounds as training set in the basis of the selected alignment. The external predictive abilities of the built models were evaluated by using the test set of nine compounds. From obtained results, the CoMSIA method was found to have highly predictive capability in comparison with CoMFA method. Based on the given results by CoMSIA and CoMFA contour maps, some features that can enhance the activity of compounds as MCD antagonists were introduced and used to design new compounds with better inhibition activity.

  11. 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

  12. 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

  13. Binding of matrix metalloproteinase inhibitors to extracellular matrix: 3D-QSAR analysis.

    Science.gov (United States)

    Zhang, Yufen; Lukacova, Viera; Bartus, Vladimir; Nie, Xiaoping; Sun, Guorong; Manivannan, Ethirajan; Ghorpade, Sandeep R; Jin, Xiaomin; Manyem, Shankar; Sibi, Mukund P; Cook, Gregory R; Balaz, Stefan

    2008-10-01

    Binding to the extracellular matrix, one of the most abundant human protein complexes, significantly affects drug disposition. Specifically, the interactions with extracellular matrix determine the free concentrations of small molecules acting in tissues, including signaling peptides, inhibitors of tissue remodeling enzymes such as matrix metalloproteinases, and other drug candidates. The nature of extracellular matrix binding was elucidated for 63 matrix metalloproteinase inhibitors, for which the association constants to an extracellular matrix mimic were reported here. The data did not correlate with lipophilicity as a common determinant of structure-nonspecific, orientation-averaged binding. A hypothetical structure of the binding site of the solidified extracellular matrix surrogate was analyzed using the Comparative Molecular Field Analysis, which needed to be applied in our multi-mode variant. This fact indicates that the compounds bind to extracellular matrix in multiple modes, which cannot be considered as completely orientation-averaged and exhibit structural dependence. The novel comparative molecular field analysis models, exhibiting satisfactory descriptive and predictive abilities, are suitable for prediction of the extracellular matrix binding for the untested chemicals, which are within applicability domains. The results contribute to a better prediction of the pharmacokinetic parameters such as the distribution volume and the tissue-blood partition coefficients, in addition to a more imminent benefit for the development of more effective matrix metalloproteinase inhibitors.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. QSAR models for anti-malarial activity of 4-aminoquinolines.

    Science.gov (United States)

    Masand, Vijay H; Toropov, Andrey A; Toropova, Alla P; Mahajan, Devidas T

    2014-03-01

    In the present study, predictive quantitative structure - activity relationship (QSAR) models for anti-malarial activity of 4-aminoquinolines have been developed. CORAL, which is freely available on internet (http://www.insilico.eu/coral), has been used as a tool of QSAR analysis to establish statistically robust QSAR model of anti-malarial activity of 4-aminoquinolines. Six random splits into the visible sub-system of the training and invisible subsystem of validation were examined. Statistical qualities for these splits vary, but in all these cases, statistical quality of prediction for anti-malarial activity was quite good. The optimal SMILES-based descriptor was used to derive the single descriptor based QSAR model for a data set of 112 aminoquinolones. All the splits had r(2)> 0.85 and r(2)> 0.78 for subtraining and validation sets, respectively. The three parametric multilinear regression (MLR) QSAR model has Q(2) = 0.83, R(2) = 0.84 and F = 190.39. The anti-malarial activity has strong correlation with presence/absence of nitrogen and oxygen at a topological distance of six.

  6. 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.

  7. 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

  8. 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

  9. 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)

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. 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

  14. 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

  15. Antitumor evaluation and 3D-QSAR studies of a new series of the spiropyrroloquinoline isoindolinone/aza-isoindolinone derivatives by comparative molecular field analysis (CoMFA).

    Science.gov (United States)

    Sadeghzadeh, Masoud; Salahinejad, Maryam; Zarezadeh, Nahid; Ghandi, Mehdi; Baghery, Maryam Keshavarz

    2017-11-01

    In current study, antitumor activity of two series of the newly synthesized spiropyrroloquinoline isoindolinone and spiropyrroloquinoline aza-isoindolinone scaffolds was evaluated against three human breast normal and cancer cell lines (MCF-10A, MCF-7 and SK-BR-3) and compared with cytotoxicity values of doxorubicin and colchicine as the standard drugs. It was found that several compounds were endowed with cytotoxicity in the low micromolar range. Among these two series, compounds 6i, 6j, 6k and 7l, 7m, 7n, 7o containing 3-ethyl-1H-indole moiety were found to be highly effective against both cancer cell lines ranging from [Formula: see text] to [Formula: see text] in comparison with the corresponding analogs. Compared with human cancer cells, the most potent compounds did not show high cytotoxicity against human breast normal MCF-10A cells. Generally, most of the evaluated compounds 6a-l and 7a-o series showed more antitumor activity against SK-BR-3 than MCF-7 cells. Moreover, comparative molecular field analysis (CoMFA) as a popular tools of three-dimensional quantitative structure-activity relationship (3D-QSAR) studies was carried out on 27 spiropyrroloquinolineisoindolinone and spiropyrroloquinolineaza-isoindolinone derivatives with antitumor activity against on SK-BR-3 cells. The obtained CoMFA models showed statistically excellent performance, which also possessed good predictive ability for an external test set. The results confirm the important effect of molecular steric and electrostatic interactions of these compounds on in vitro cytotoxicity against SK-BR-3.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. 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.

  7. 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.

  8. Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR theories.

    Science.gov (United States)

    Mercader, Andrew G; Duchowicz, Pablo R; Fernández, Francisco M; Castro, Eduardo A

    2010-09-27

    We compare three methods for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. On the one hand is our enhanced replacement method (ERM) and on the other is the simpler replacement method (RM) and the genetic algorithm (GA). These methods avoid the impracticable full search for optimal variables in large sets of molecular descriptors. Present results for 10 different experimental databases suggest that the ERM is clearly preferable to the GA that is slightly better than the RM. However, the latter approach requires the smallest amount of linear regressions and, consequently, the lowest computation time.

  9. 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.

  10. 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.

  11. 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%.

  12. 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.

  13. 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

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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. ∗.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. The surface analysis methods

    International Nuclear Information System (INIS)

    Deville, J.P.

    1998-01-01

    Nowadays, there are a lot of surfaces analysis methods, each having its specificity, its qualities, its constraints (for instance vacuum) and its limits. Expensive in time and in investment, these methods have to be used deliberately. This article appeals to non specialists. It gives some elements of choice according to the studied information, the sensitivity, the use constraints or the answer to a precise question. After having recalled the fundamental principles which govern these analysis methods, based on the interaction between radiations (ultraviolet, X) or particles (ions, electrons) with matter, two methods will be more particularly described: the Auger electron spectroscopy (AES) and x-rays photoemission spectroscopy (ESCA or XPS). Indeed, they are the most widespread methods in laboratories, the easier for use and probably the most productive for the analysis of surface of industrial materials or samples submitted to treatments in aggressive media. (O.M.)

  16. 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.

  17. Methods of Multivariate Analysis

    CERN Document Server

    Rencher, Alvin C

    2012-01-01

    Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit

  18. 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.

  19. 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.

  20. 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.

  1. Methods for RNA Analysis

    DEFF Research Database (Denmark)

    Olivarius, Signe

    of the transcriptome, 5’ end capture of RNA is combined with next-generation sequencing for high-throughput quantitative assessment of transcription start sites by two different methods. The methods presented here allow for functional investigation of coding as well as noncoding RNA and contribute to future...... RNAs rely on interactions with proteins, the establishment of protein-binding profiles is essential for the characterization of RNAs. Aiming to facilitate RNA analysis, this thesis introduces proteomics- as well as transcriptomics-based methods for the functional characterization of RNA. First, RNA...

  2. 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.

  3. Analysis of numerical methods

    CERN Document Server

    Isaacson, Eugene

    1994-01-01

    This excellent text for advanced undergraduates and graduate students covers norms, numerical solution of linear systems and matrix factoring, iterative solutions of nonlinear equations, eigenvalues and eigenvectors, polynomial approximation, and other topics. It offers a careful analysis and stresses techniques for developing new methods, plus many examples and problems. 1966 edition.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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

  7. 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.

  8. 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.

  9. 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...

  10. 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

  11. 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.

  12. Methods for Risk Analysis

    International Nuclear Information System (INIS)

    Alverbro, Karin

    2010-01-01

    Many decision-making situations today affect humans and the environment. In practice, many such decisions are made without an overall view and prioritise one or other of the two areas. Now and then these two areas of regulation come into conflict, e.g. the best alternative as regards environmental considerations is not always the best from a human safety perspective and vice versa. This report was prepared within a major project with the aim of developing a framework in which both the environmental aspects and the human safety aspects are integrated, and decisions can be made taking both fields into consideration. The safety risks have to be analysed in order to be successfully avoided and one way of doing this is to use different kinds of risk analysis methods. There is an abundance of existing methods to choose from and new methods are constantly being developed. This report describes some of the risk analysis methods currently available for analysing safety and examines the relationships between them. The focus here is mainly on human safety aspects

  13. 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

  14. 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

  15. 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.

  16. Comparative analysis of QSAR models for predicting pK(a) of organic oxygen acids and nitrogen bases from molecular structure.

    Science.gov (United States)

    Yu, Haiying; Kühne, Ralph; Ebert, Ralf-Uwe; Schüürmann, Gerrit

    2010-11-22

    For 1143 organic compounds comprising 580 oxygen acids and 563 nitrogen bases that cover more than 17 orders of experimental pK(a) (from -5.00 to 12.23), the pK(a) prediction performances of ACD, SPARC, and two calibrations of a semiempirical quantum chemical (QC) AM1 approach have been analyzed. The overall root-mean-square errors (rms) for the acids are 0.41, 0.58 (0.42 without ortho-substituted phenols with intramolecular H-bonding), and 0.55 and for the bases are 0.65, 0.70, 1.17, and 1.27 for ACD, SPARC, and both QC methods, respectively. Method-specific performances are discussed in detail for six acid subsets (phenols and aromatic and aliphatic carboxylic acids with different substitution patterns) and nine base subsets (anilines, primary, secondary and tertiary amines, meta/para-substituted and ortho-substituted pyridines, pyrimidines, imidazoles, and quinolines). The results demonstrate an overall better performance for acids than for bases but also a substantial variation across subsets. For the overall best-performing ACD, rms ranges from 0.12 to 1.11 and 0.40 to 1.21 pK(a) units for the acid and base subsets, respectively. With regard to the squared correlation coefficient r², the results are 0.86 to 0.96 (acids) and 0.79 to 0.95 (bases) for ACD, 0.77 to 0.95 (acids) and 0.85 to 0.97 (bases) for SPARC, and 0.64 to 0.87 (acids) and 0.43 to 0.83 (bases) for the QC methods, respectively. Attention is paid to structural and method-specific causes for observed pitfalls. The significant subset dependence of the prediction performances suggests a consensus modeling approach.

  17. 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

  18. Method of signal analysis

    International Nuclear Information System (INIS)

    Berthomier, Charles

    1975-01-01

    A method capable of handling the amplitude and the frequency time laws of a certain kind of geophysical signals is described here. This method is based upon the analytical signal idea of Gabor and Ville, which is constructed either in the time domain by adding an imaginary part to the real signal (in-quadrature signal), or in the frequency domain by suppressing negative frequency components. The instantaneous frequency of the initial signal is then defined as the time derivative of the phase of the analytical signal, and his amplitude, or envelope, as the modulus of this complex signal. The method is applied to three types of magnetospheric signals: chorus, whistlers and pearls. The results obtained by analog and numerical calculations are compared to results obtained by classical systems using filters, i.e. based upon a different definition of the concept of frequency. The precision with which the frequency-time laws are determined leads then to the examination of the principle of the method and to a definition of instantaneous power density spectrum attached to the signal, and to the first consequences of this definition. In this way, a two-dimensional representation of the signal is introduced which is less deformed by the analysis system properties than the usual representation, and which moreover has the advantage of being obtainable practically in real time [fr

  19. 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.

  20. Methods for geochemical analysis

    Science.gov (United States)

    Baedecker, Philip A.

    1987-01-01

    The laboratories for analytical chemistry within the Geologic Division of the U.S. Geological Survey are administered by the Office of Mineral Resources. The laboratory analysts provide analytical support to those programs of the Geologic Division that require chemical information and conduct basic research in analytical and geochemical areas vital to the furtherance of Division program goals. Laboratories for research and geochemical analysis are maintained at the three major centers in Reston, Virginia, Denver, Colorado, and Menlo Park, California. The Division has an expertise in a broad spectrum of analytical techniques, and the analytical research is designed to advance the state of the art of existing techniques and to develop new methods of analysis in response to special problems in geochemical analysis. The geochemical research and analytical results are applied to the solution of fundamental geochemical problems relating to the origin of mineral deposits and fossil fuels, as well as to studies relating to the distribution of elements in varied geologic systems, the mechanisms by which they are transported, and their impact on the environment.

  1. 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....

  2. 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...

  3. 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...

  4. COMPUTER METHODS OF GENETIC ANALYSIS.

    Directory of Open Access Journals (Sweden)

    A. L. Osipov

    2017-02-01

    Full Text Available The basic statistical methods used in conducting the genetic analysis of human traits. We studied by segregation analysis, linkage analysis and allelic associations. Developed software for the implementation of these methods support.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. Multipotent cholinesterase/monoamine oxidase inhibitors for the treatment of Alzheimer's disease: design, synthesis, biochemical evaluation, ADMET, molecular modeling, and QSAR analysis of novel donepezil-pyridyl hybrids.

    Science.gov (United States)

    Bautista-Aguilera, Oscar M; Esteban, Gerard; Chioua, Mourad; Nikolic, Katarina; Agbaba, Danica; Moraleda, Ignacio; Iriepa, Isabel; Soriano, Elena; Samadi, Abdelouahid; Unzeta, Mercedes; Marco-Contelles, José

    2014-01-01

    The design, synthesis, and biochemical evaluation of donepezil-pyridyl hybrids (DPHs) as multipotent cholinesterase (ChE) and monoamine oxidase (MAO) inhibitors for the potential treatment of Alzheimer's disease (AD) is reported. The 3D-quantitative structure-activity relationship study was used to define 3D-pharmacophores for inhibition of MAO A/B, acetylcholinesterase (AChE), and butyrylcholinesterase (BuChE) enzymes and to design DPHs as novel multi-target drug candidates with potential impact in the therapy of AD. DPH14 (Electrophorus electricus AChE [EeAChE]: half maximal inhibitory concentration [IC50] =1.1±0.3 nM; equine butyrylcholinesterase [eqBuChE]: IC50 =600±80 nM) was 318-fold more potent for the inhibition of AChE, and 1.3-fold less potent for the inhibition of BuChE than the reference compound ASS234. DPH14 is a potent human recombinant BuChE (hBuChE) inhibitor, in the same range as DPH12 or DPH16, but 13.1-fold less potent than DPH15 for the inhibition of human recombinant AChE (hAChE). Compared with donepezil, DPH14 is almost equipotent for the inhibition of hAChE, and 8.8-fold more potent for hBuChE. Concerning human monoamine oxidase (hMAO) A inhibition, only DPH9 and 5 proved active, compound DPH9 being the most potent (IC50 [MAO A] =5,700±2,100 nM). For hMAO B, only DPHs 13 and 14 were moderate inhibitors, and compound DPH14 was the most potent (IC50 [MAO B] =3,950±940 nM). Molecular modeling of inhibitor DPH14 within EeAChE showed a binding mode with an extended conformation, interacting simultaneously with both catalytic and peripheral sites of EeAChE thanks to a linker of appropriate length. Absortion, distribution, metabolism, excretion and toxicity analysis showed that structures lacking phenyl-substituent show better druglikeness profiles; in particular, DPHs13-15 showed the most suitable absortion, distribution, metabolism, excretion and toxicity properties. Novel donepezil-pyridyl hybrid DPH14 is a potent, moderately selective h

  8. 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.

  9. 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.

  10. Multipotent cholinesterase/monoamine oxidase inhibitors for the treatment of Alzheimer’s disease: design, synthesis, biochemical evaluation, ADMET, molecular modeling, and QSAR analysis of novel donepezil-pyridyl hybrids

    Directory of Open Access Journals (Sweden)

    Bautista-Aguilera OM

    2014-10-01

    BuChE. Concerning human monoamine oxidase (hMAO A inhibition, only DPH9 and 5 proved active, compound DPH9 being the most potent (IC50 [MAO A] =5,700±2,100 nM. For hMAO B, only DPHs 13 and 14 were moderate inhibitors, and compound DPH14 was the most potent (IC50 [MAO B] =3,950±940 nM. Molecular modeling of inhibitor DPH14 within EeAChE showed a binding mode with an extended conformation, interacting simultaneously with both catalytic and peripheral sites of EeAChE thanks to a linker of appropriate length. Absortion, distribution, metabolism, excretion and toxicity analysis showed that structures lacking phenyl-substituent show better druglikeness profiles; in particular, DPHs13–15 showed the most suitable absortion, distribution, metabolism, excretion and toxicity properties. Novel donepezil-pyridyl hybrid DPH14 is a potent, moderately selective hAChE and selective irreversible hMAO B inhibitor which might be considered as a promising compound for further development for the treatment of AD. Keywords: donepezil-pyridyl hybrids, ChE, MAO, 3D-QSAR, molecular modeling, ADMET

  11. 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...

  12. 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.

  13. Methods of nonlinear analysis

    CERN Document Server

    Bellman, Richard Ernest

    1970-01-01

    In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank mat

  14. 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...

  15. 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.

  16. 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

  17. 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...

  18. Multivariate analysis: models and method

    International Nuclear Information System (INIS)

    Sanz Perucha, J.

    1990-01-01

    Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

  19. Multivariate analysis methods in physics

    International Nuclear Information System (INIS)

    Wolter, M.

    2007-01-01

    A review of multivariate methods based on statistical training is given. Several multivariate methods useful in high-energy physics analysis are discussed. Selected examples from current research in particle physics are discussed, both from the on-line trigger selection and from the off-line analysis. Also statistical training methods are presented and some new application are suggested [ru

  20. Methods in algorithmic analysis

    CERN Document Server

    Dobrushkin, Vladimir A

    2009-01-01

    …helpful to any mathematics student who wishes to acquire a background in classical probability and analysis … This is a remarkably beautiful book that would be a pleasure for a student to read, or for a teacher to make into a year's course.-Harvey Cohn, Computing Reviews, May 2010

  1. Communication Network Analysis Methods.

    Science.gov (United States)

    Farace, Richard V.; Mabee, Timothy

    This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

  2. Complementing Gender Analysis Methods.

    Science.gov (United States)

    Kumar, Anant

    2016-01-01

    The existing gender analysis frameworks start with a premise that men and women are equal and should be treated equally. These frameworks give emphasis on equal distribution of resources between men and women and believe that this will bring equality which is not always true. Despite equal distribution of resources, women tend to suffer and experience discrimination in many areas of their lives such as the power to control resources within social relationships, and the need for emotional security and reproductive rights within interpersonal relationships. These frameworks believe that patriarchy as an institution plays an important role in women's oppression, exploitation, and it is a barrier in their empowerment and rights. Thus, some think that by ensuring equal distribution of resources and empowering women economically, institutions like patriarchy can be challenged. These frameworks are based on proposed equality principle which puts men and women in competing roles. Thus, the real equality will never be achieved. Contrary to the existing gender analysis frameworks, the Complementing Gender Analysis framework proposed by the author provides a new approach toward gender analysis which not only recognizes the role of economic empowerment and equal distribution of resources but suggests to incorporate the concept and role of social capital, equity, and doing gender in gender analysis which is based on perceived equity principle, putting men and women in complementing roles that may lead to equality. In this article the author reviews the mainstream gender theories in development from the viewpoint of the complementary roles of gender. This alternative view is argued based on existing literature and an anecdote of observations made by the author. While criticizing the equality theory, the author offers equity theory in resolving the gender conflict by using the concept of social and psychological capital.

  3. 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.

  4. 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

  5. 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...

  6. STOCHASTIC METHODS IN RISK ANALYSIS

    Directory of Open Access Journals (Sweden)

    Vladimíra OSADSKÁ

    2017-06-01

    Full Text Available In this paper, we review basic stochastic methods which can be used to extend state-of-the-art deterministic analytical methods for risk analysis. We can conclude that the standard deterministic analytical methods highly depend on the practical experience and knowledge of the evaluator and therefore, the stochastic methods should be introduced. The new risk analysis methods should consider the uncertainties in input values. We present how large is the impact on the results of the analysis solving practical example of FMECA with uncertainties modelled using Monte Carlo sampling.

  7. 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.

  8. 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

  9. Quantitative structure-activity relationship analysis to elucidate the clearance mechanisms of Tc-99m labeled quinolone antibiotics

    International Nuclear Information System (INIS)

    Salahinejad, M.; Mirshojaei, S.F.

    2016-01-01

    This study aims to establish molecular modeling methods for predicting the liver and kidney uptakes of Tc-99m labeled quinolone antibiotics. Some three-dimensional quantitative-activity relationships (3D-QSAR) models were developed using comparative molecular field analysis and grid-independent descriptors procedures. As a first report on 3D-QSAR modeling, the predicted liver and kidney uptakes for quinolone antibiotics were in good agreement with the experimental values. The obtained results confirm the importance of hydrophobic interactions, size and steric hindrance of antibiotic molecules in their liver uptakes, while the electrostatic interactions and hydrogen bonding ability have impressive effects on their kidney uptakes. (author)

  10. Basic methods of isotope analysis

    International Nuclear Information System (INIS)

    Ochkin, A.V.; Rozenkevich, M.B.

    2000-01-01

    The bases of the most applied methods of the isotope analysis are briefly presented. The possibilities and analytical characteristics of the mass-spectrometric, spectral, radiochemical and special methods of the isotope analysis, including application of the magnetic resonance, chromatography and refractometry, are considered [ru

  11. 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

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Probabilistic methods for rotordynamics analysis

    Science.gov (United States)

    Wu, Y.-T.; Torng, T. Y.; Millwater, H. R.; Fossum, A. F.; Rheinfurth, M. H.

    1991-01-01

    This paper summarizes the development of the methods and a computer program to compute the probability of instability of dynamic systems that can be represented by a system of second-order ordinary linear differential equations. Two instability criteria based upon the eigenvalues or Routh-Hurwitz test functions are investigated. Computational methods based on a fast probability integration concept and an efficient adaptive importance sampling method are proposed to perform efficient probabilistic analysis. A numerical example is provided to demonstrate the methods.

  20. 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).

  1. Analysis of Precision of Activation Analysis Method

    DEFF Research Database (Denmark)

    Heydorn, Kaj; Nørgaard, K.

    1973-01-01

    The precision of an activation-analysis method prescribes the estimation of the precision of a single analytical result. The adequacy of these estimates to account for the observed variation between duplicate results from the analysis of different samples and materials, is tested by the statistic T...

  2. Analysis apparatus and method of analysis

    International Nuclear Information System (INIS)

    1976-01-01

    A continuous streaming method developed for the excution of immunoassays is described in this patent. In addition, a suitable apparatus for the method was developed whereby magnetic particles are automatically employed for the consecutive analysis of a series of liquid samples via the RIA technique

  3. Nonlinear programming analysis and methods

    CERN Document Server

    Avriel, Mordecai

    2012-01-01

    This text provides an excellent bridge between principal theories and concepts and their practical implementation. Topics include convex programming, duality, generalized convexity, analysis of selected nonlinear programs, techniques for numerical solutions, and unconstrained optimization methods.

  4. Chemical methods of rock analysis

    National Research Council Canada - National Science Library

    Jeffery, P. G; Hutchison, D

    1981-01-01

    A practical guide to the methods in general use for the complete analysis of silicate rock material and for the determination of all those elements present in major, minor or trace amounts in silicate...

  5. Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

    Science.gov (United States)

    Hsing, Michael; Byler, Kendall; Cherkasov, Artem

    2009-01-01

    Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. Seismic design and analysis methods

    International Nuclear Information System (INIS)

    Varpasuo, P.

    1993-01-01

    Seismic load is in many areas of the world the most important loading situation from the point of view of structural strength. Taking this into account it is understandable, that there has been a strong allocation of resources in the seismic analysis during the past ten years. In this study there are three areas of the center of gravity: (1) Random vibrations; (2) Soil-structure interaction and (3) The methods for determining structural response. The solution of random vibration problems is clarified with the aid of applications in this study and from the point of view of mathematical treatment and mathematical formulations it is deemed sufficient to give the relevant sources. In the soil-structure interaction analysis the focus has been the significance of frequency dependent impedance functions. As a result it was obtained, that the description of the soil with the aid of frequency dependent impedance functions decreases the structural response and it is thus always the preferred method when compared to more conservative analysis types. From the methods to determine the C structural response the following four were tested: (1) The time history method; (2) The complex frequency-response method; (3) Response spectrum method and (4) The equivalent static force method. The time history appeared to be the most accurate method and the complex frequency-response method did have the widest area of application. (orig.). (14 refs., 35 figs.)

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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.

    Science.gov (United States)

    Sanderson, Hans; Thomsen, Marianne

    2009-06-01

    Pharmaceuticals have been reported to be ubiquitously present in surface waters prompting concerns of effects of these bioactive substances. Meanwhile, there is a general scarcity of publicly available ecotoxicological data concerning pharmaceuticals. The aim of this paper was to compile 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 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% of the pharmaceuticals have a non-specific MOA. Additionally, the acute-to-chronic ratio (ACR) for 70% of the analyzed pharmaceuticals was below 25 further suggesting a non-specific MOA. Sub-lethal receptor-mediated effects may however have a more specific MOA.

  15. 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.

  16. 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.

  17. Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

    Science.gov (United States)

    Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

    1998-03-01

    Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

  18. Design, synthesis, pharmacological evaluation, QSAR analysis, molecular modeling and ADMET of novel donepezil-indolyl hybrids as multipotent cholinesterase/monoamine oxidase inhibitors for the potential treatment of Alzheimer's disease.

    Science.gov (United States)

    Bautista-Aguilera, Oscar M; Esteban, Gerard; Bolea, Irene; Nikolic, Katarina; Agbaba, Danica; Moraleda, Ignacio; Iriepa, Isabel; Samadi, Abdelouahid; Soriano, Elena; Unzeta, Mercedes; Marco-Contelles, José

    2014-03-21

    The design, synthesis, and pharmacological evaluation of donepezil-indolyl based amines 7-10, amides 12-16, and carboxylic acid derivatives 5 and 11, as multipotent ASS234 analogs, able to inhibit simultaneously cholinesterase (ChE) and monoamine oxidase (MAO) enzymes for the potential treatment of Alzheimer's disease (AD), is reported. Theoretical studies using 3D-Quantitative Structure-Activity Relationship (3D-QSAR) was used to define 3D-pharmacophores for inhibition of MAO A/B, AChE, and BuChE enzymes. We found that, in general, and for the same substituent, amines are more potent ChE inhibitors (see compounds 12, 13 versus 7 and 8) or equipotent (see compounds 14, 15 versus 9 and 10) than the corresponding amides, showing a clear EeAChE inhibition selectivity. For the MAO inhibition, amides were not active, and among the amines, compound 14 was totally MAO A selective, while amines 15 and 16 were quite MAO A selective. Carboxylic acid derivatives 5 and 11 showed a multipotent moderate selective profile as EeACE and MAO A inhibitors. Propargylamine 15 [N-((5-(3-(1-benzylpiperidin-4-yl)propoxy)-1-methyl-1H-indol-2-yl)methyl)prop-2-yn-1-amine] resulted in the most potent hMAO A (IC50 = 5.5 ± 1.4 nM) and moderately potent hMAO B (IC50 = 150 ± 31 nM), EeAChE (IC50 = 190 ± 10 nM), and eqBuChE (IC50 = 830 ± 160 nM) inhibitor. However, the analogous N-allyl and the N-morpholine derivatives 16 and 14 deserve also attention as they show an attractive multipotent profile. To sum up, donepezil-indolyl hybrid 15 is a promising drug for further development for the potential prevention and treatment of AD. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. SWOT ANALYSIS ON SAMPLING METHOD

    Directory of Open Access Journals (Sweden)

    CHIS ANCA OANA

    2014-07-01

    Full Text Available Audit sampling involves the application of audit procedures to less than 100% of items within an account balance or class of transactions. Our article aims to study audit sampling in audit of financial statements. As an audit technique largely used, in both its statistical and nonstatistical form, the method is very important for auditors. It should be applied correctly for a fair view of financial statements, to satisfy the needs of all financial users. In order to be applied correctly the method must be understood by all its users and mainly by auditors. Otherwise the risk of not applying it correctly would cause loose of reputation and discredit, litigations and even prison. Since there is not a unitary practice and methodology for applying the technique, the risk of incorrectly applying it is pretty high. The SWOT analysis is a technique used that shows the advantages, disadvantages, threats and opportunities. We applied SWOT analysis in studying the sampling method, from the perspective of three players: the audit company, the audited entity and users of financial statements. The study shows that by applying the sampling method the audit company and the audited entity both save time, effort and money. The disadvantages of the method are difficulty in applying and understanding its insight. Being largely used as an audit method and being a factor of a correct audit opinion, the sampling method’s advantages, disadvantages, threats and opportunities must be understood by auditors.

  4. 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.

  5. Flows method in global analysis

    International Nuclear Information System (INIS)

    Duong Minh Duc.

    1994-12-01

    We study the gradient flows method for W r,p (M,N) where M and N are Riemannian manifold and r may be less than m/p. We localize some global analysis problem by constructing gradient flows which only change the value of any u in W r,p (M,N) in a local chart of M. (author). 24 refs

  6. 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

  7. Data Analysis Methods for Paleogenomics

    DEFF Research Database (Denmark)

    Avila Arcos, Maria del Carmen

    (Danmarks Grundforskningfond) 'Centre of Excellence in GeoGenetics' grant, with additional funding provided by the Danish Council for Independent Research 'Sapere Aude' programme. The thesis comprises five chapters, all of which represent different projects that involved the analysis of massive amounts......, thanks to the introduction of NGS and the implementation of data analysis methods specific for each project. Chapters 1 to 3 have been published in peer-reviewed journals and Chapter 4 is currently in review. Chapter 5 consists of a manuscript describing initial results of an ongoing research project......The work presented in this thesis is the result of research carried out during a three-year PhD at the Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, under supervision of Professor Tom Gilbert. The PhD was funded by the Danish National Research Foundation...

  8. A New Boron Analysis Method

    Energy Technology Data Exchange (ETDEWEB)

    Weitman, J; Daaverhoeg, N; Farvolden, S

    1970-07-01

    In connection with fast neutron (n, {alpha}) cross section measurements a novel boron analysis method has been developed. The boron concentration is inferred from the mass spectrometrically determined number of helium atoms produced in the thermal and epithermal B-10 (n, {alpha}) reaction. The relation between helium amount and boron concentration is given, including corrections for self shielding effects and background levels. Direct and diffusion losses of helium are calculated and losses due to gettering, adsorption and HF-ionization in the release stage are discussed. A series of boron determinations is described and the results are compared with those obtained by other methods, showing excellent agreement. The lower limit of boron concentration which can be measured varies with type of sample. In e.g. steel, concentrations below 10-5 % boron in samples of 0.1-1 gram may be determined.

  9. 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.

  10. 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.

  11. 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.

  12. COMPETITIVE INTELLIGENCE ANALYSIS - SCENARIOS METHOD

    Directory of Open Access Journals (Sweden)

    Ivan Valeriu

    2014-07-01

    Full Text Available Keeping a company in the top performing players in the relevant market depends not only on its ability to develop continually, sustainably and balanced, to the standards set by the customer and competition, but also on the ability to protect its strategic information and to know in advance the strategic information of the competition. In addition, given that economic markets, regardless of their profile, enable interconnection not only among domestic companies, but also between domestic companies and foreign companies, the issue of economic competition moves from the national economies to the field of interest of regional and international economic organizations. The stakes for each economic player is to keep ahead of the competition and to be always prepared to face market challenges. Therefore, it needs to know as early as possible, how to react to others’ strategy in terms of research, production and sales. If a competitor is planning to produce more and cheaper, then it must be prepared to counteract quickly this movement. Competitive intelligence helps to evaluate the capabilities of competitors in the market, legally and ethically, and to develop response strategies. One of the main goals of the competitive intelligence is to acknowledge the role of early warning and prevention of surprises that could have a major impact on the market share, reputation, turnover and profitability in the medium and long term of a company. This paper presents some aspects of competitive intelligence, mainly in terms of information analysis and intelligence generation. Presentation is theoretical and addresses a structured method of information analysis - scenarios method – in a version that combines several types of analysis in order to reveal some interconnecting aspects of the factors governing the activity of a company.

  13. Gravimetric and titrimetric methods of analysis

    International Nuclear Information System (INIS)

    Rives, R.D.; Bruks, R.R.

    1983-01-01

    Gravimetric and titrimetric methods of analysis are considered. Methods of complexometric titration are mentioned, as well as methods of increasing sensitivity in titrimetry. Gravimetry and titrimetry are applied during analysis for traces of geological materials

  14. Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds

    Science.gov (United States)

    Marrero-Ponce, Yovani; Meneses-Marcel, Alfredo; Rivera-Borroto, Oscar M.; García-Domenech, Ramón; De Julián-Ortiz, Jesus Vicente; Montero, Alina; Escario, José Antonio; Barrio, Alicia Gómez; Pereira, David Montero; Nogal, Juan José; Grau, Ricardo; Torrens, Francisco; Vogel, Christian; Arán, Vicente J.

    2008-08-01

    Trichomonas vaginalis ( Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients ( C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show

  15. 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

  16. Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

    Science.gov (United States)

    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

  17. 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...

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 3D-QSAR Studies on Barbituric Acid Derivatives as Urease Inhibitors and the Effect of Charges on the Quality of a Model

    Directory of Open Access Journals (Sweden)

    Zaheer Ul-Haq

    2016-04-01

    Full Text Available Urease enzyme (EC 3.5.1.5 has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship advance studies were performed by Comparative Molecular Field Analysis (CoMFA and Comparative Molecular Similarity Indices Analysis (CoMSIA methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q2 value of 0.597 and correlation coefficients (r2 of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q2 and r2 of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r2pred ≥ 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity.

  3. 3D-QSAR Studies on Barbituric Acid Derivatives as Urease Inhibitors and the Effect of Charges on the Quality of a Model.

    Science.gov (United States)

    Ul-Haq, Zaheer; Ashraf, Sajda; Al-Majid, Abdullah Mohammed; Barakat, Assem

    2016-04-30

    Urease enzyme (EC 3.5.1.5) has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship) advance studies were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q²) value of 0.597 and correlation coefficients (r²) of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q² and r² of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r²pred ≥ 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity.

  4. 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.

  5. 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

  6. 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

  7. 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

    Directory of Open Access Journals (Sweden)

    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.

  8. 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.

  9. Analysis methods (from 301 to 351)

    International Nuclear Information System (INIS)

    Analysis methods of materials used in the nuclear field (uranium, plutonium and their compounds, zirconium, magnesium, water...) and determination of impurities. Only reliable methods are selected [fr

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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.

  12. 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.

  13. 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 r2pred 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.

  14. DTI analysis methods : Voxel-based analysis

    NARCIS (Netherlands)

    Van Hecke, Wim; Leemans, Alexander; Emsell, Louise

    2016-01-01

    Voxel-based analysis (VBA) of diffusion tensor imaging (DTI) data permits the investigation of voxel-wise differences or changes in DTI metrics in every voxel of a brain dataset. It is applied primarily in the exploratory analysis of hypothesized group-level alterations in DTI parameters, as it does

  15. Bayesian methods for data analysis

    CERN Document Server

    Carlin, Bradley P.

    2009-01-01

    Approaches for statistical inference Introduction Motivating Vignettes Defining the Approaches The Bayes-Frequentist Controversy Some Basic Bayesian Models The Bayes approach Introduction Prior Distributions Bayesian Inference Hierarchical Modeling Model Assessment Nonparametric Methods Bayesian computation Introduction Asymptotic Methods Noniterative Monte Carlo Methods Markov Chain Monte Carlo Methods Model criticism and selection Bayesian Modeling Bayesian Robustness Model Assessment Bayes Factors via Marginal Density Estimation Bayes Factors

  16. 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

  17. 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 ...

  18. 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

  19. 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...

  20. 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...

  1. Substoichiometric method in the simple radiometric analysis

    International Nuclear Information System (INIS)

    Ikeda, N.; Noguchi, K.

    1979-01-01

    The substoichiometric method is applied to simple radiometric analysis. Two methods - the standard reagent method and the standard sample method - are proposed. The validity of the principle of the methods is verified experimentally in the determination of silver by the precipitation method, or of zinc by the ion-exchange or solvent-extraction method. The proposed methods are simple and rapid compared with the conventional superstoichiometric method. (author)

  2. 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.

  3. 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.

  4. 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....

  5. Chemical methods of rock analysis

    National Research Council Canada - National Science Library

    Jeffery, P. G; Hutchison, D

    1981-01-01

    .... Such methods include those based upon spectrophotometry, flame emission spectrometry and atomic absorption spectroscopy, as well as gravimetry, titrimetry and the use of ion-selective electrodes...

  6. (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.

  7. 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.

  8. Probabilistic methods in combinatorial analysis

    CERN Document Server

    Sachkov, Vladimir N

    2014-01-01

    This 1997 work explores the role of probabilistic methods for solving combinatorial problems. These methods not only provide the means of efficiently using such notions as characteristic and generating functions, the moment method and so on but also let us use the powerful technique of limit theorems. The basic objects under investigation are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these specify the probabilist

  9. Methods in quantitative image analysis.

    Science.gov (United States)

    Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

    1996-05-01

    The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value

  10. 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.

  11. Moyer's method of mixed dentition analysis: a meta-analysis ...

    African Journals Online (AJOL)

    The applicability of tables derived from the data Moyer used to other ethnic groups has ... This implies that Moyer's method of prediction may have population variations. ... Key Words: meta-analysis, mixed dentition analysis, Moyer's method

  12. 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.

  13. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    Science.gov (United States)

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  14. Applying critical analysis - main methods

    Directory of Open Access Journals (Sweden)

    Miguel Araujo Alonso

    2012-02-01

    Full Text Available What is the usefulness of critical appraisal of literature? Critical analysis is a fundamental condition for the correct interpretation of any study that is subject to review. In epidemiology, in order to learn how to read a publication, we must be able to analyze it critically. Critical analysis allows us to check whether a study fulfills certain previously established methodological inclusion and exclusion criteria. This is frequently used in conducting systematic reviews although eligibility criteria are generally limited to the study design. Critical analysis of literature and be done implicitly while reading an article, as in reading for personal interest, or can be conducted in a structured manner, using explicit and previously established criteria. The latter is done when formally reviewing a topic.

  15. Trial Sequential Methods for Meta-Analysis

    Science.gov (United States)

    Kulinskaya, Elena; Wood, John

    2014-01-01

    Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…

  16. Hybrid methods for cybersecurity analysis :

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Warren Leon,; Dunlavy, Daniel M.

    2014-01-01

    Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and

  17. Microparticle analysis system and method

    Science.gov (United States)

    Morrison, Dennis R. (Inventor)

    2007-01-01

    A device for analyzing microparticles is provided which includes a chamber with an inlet and an outlet for respectively introducing and dispensing a flowing fluid comprising microparticles, a light source for providing light through the chamber and a photometer for measuring the intensity of light transmitted through individual microparticles. The device further includes an imaging system for acquiring images of the fluid. In some cases, the device may be configured to identify and determine a quantity of the microparticles within the fluid. Consequently, a method for identifying and tracking microparticles in motion is contemplated herein. The method involves flowing a fluid comprising microparticles in laminar motion through a chamber, transmitting light through the fluid, measuring the intensities of the light transmitted through the microparticles, imaging the fluid a plurality of times and comparing at least some of the intensities of light between different images of the fluid.

  18. Infinitesimal methods of mathematical analysis

    CERN Document Server

    Pinto, J S

    2004-01-01

    This modern introduction to infinitesimal methods is a translation of the book Métodos Infinitesimais de Análise Matemática by José Sousa Pinto of the University of Aveiro, Portugal and is aimed at final year or graduate level students with a background in calculus. Surveying modern reformulations of the infinitesimal concept with a thoroughly comprehensive exposition of important and influential hyperreal numbers, the book includes previously unpublished material on the development of hyperfinite theory of Schwartz distributions and its application to generalised Fourier transforms and harmon

  19. Development of advanced MCR task analysis methods

    International Nuclear Information System (INIS)

    Na, J. C.; Park, J. H.; Lee, S. K.; Kim, J. K.; Kim, E. S.; Cho, S. B.; Kang, J. S.

    2008-07-01

    This report describes task analysis methodology for advanced HSI designs. Task analyses was performed by using procedure-based hierarchical task analysis and task decomposition methods. The results from the task analysis were recorded in a database. Using the TA results, we developed static prototype of advanced HSI and human factors engineering verification and validation methods for an evaluation of the prototype. In addition to the procedure-based task analysis methods, workload estimation based on the analysis of task performance time and analyses for the design of information structure and interaction structures will be necessary

  20. 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

  1. Current status of methods for shielding analysis

    International Nuclear Information System (INIS)

    Engle, W.W.

    1980-01-01

    Current methods used in shielding analysis and recent improvements in those methods are discussed. The status of methods development is discussed based on needs cited at the 1977 International Conference on Reactor Shielding. Additional areas where methods development is needed are discussed

  2. Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture

    Science.gov (United States)

    West, Phillip B [Idaho Falls, ID; Novascone, Stephen R [Idaho Falls, ID; Wright, Jerry P [Idaho Falls, ID

    2011-09-27

    Earth analysis methods, subsurface feature detection methods, earth analysis devices, and articles of manufacture are described. According to one embodiment, an earth analysis method includes engaging a device with the earth, analyzing the earth in a single substantially lineal direction using the device during the engaging, and providing information regarding a subsurface feature of the earth using the analysis.

  3. Parametric Methods for Order Tracking Analysis

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm

    2017-01-01

    Order tracking analysis is often used to find the critical speeds at which structural resonances are excited by a rotating machine. Typically, order tracking analysis is performed via non-parametric methods. In this report, however, we demonstrate some of the advantages of using a parametric method...

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

    Science.gov (United States)

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

    2014-10-01

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

  5. The delayed neutron method of uranium analysis

    International Nuclear Information System (INIS)

    Wall, T.

    1989-01-01

    The technique of delayed neutron analysis (DNA) is discussed. The DNA rig installed on the MOATA reactor, the assay standards and the types of samples which have been assayed are described. Of the total sample throughput of about 55,000 units since the uranium analysis service began, some 78% has been concerned with analysis of uranium ore samples derived from mining and exploration. Delayed neutron analysis provides a high sensitivity, low cost uranium analysis method for both uranium exploration and other applications. It is particularly suitable for analysis of large batch samples and for non-destructive analysis over a wide range of matrices. 8 refs., 4 figs., 3 tabs

  6. In Vitro Antioxidant Activity of Selected 4-Hydroxy-chromene-2-one Derivatives—SAR, QSAR and DFT Studies

    Directory of Open Access Journals (Sweden)

    Slavica Solujić

    2011-04-01

    Full Text Available The series of fifteen synthesized 4-hydroxycoumarin derivatives was subjected to antioxidant activity evaluation in vitro, through total antioxidant capacity, 1,1-diphenyl-2-picryl-hydrazyl (DPPH, hydroxyl radical, lipid peroxide scavenging and chelating activity. The highest activity was detected during the radicals scavenging, with 2b, 6b, 2c, and 4c noticed as the most active. The antioxidant activity was further quantified by the quantitative structure-activity relationships (QSAR studies. For this purpose, the structures were optimized using Paramethric Method 6 (PM6 semi-empirical and Density Functional Theory (DFT B3LYP methods. Bond dissociation enthalpies of coumarin 4-OH, Natural Bond Orbital (NBO gained hybridization of the oxygen, acidity of the hydrogen atom and various molecular descriptors obtained, were correlated with biological activity, after which we designed 20 new antioxidant structures, using the most favorable structural motifs, with much improved predicted activity in vitro.

  7. Radiochemistry and nuclear methods of analysis

    International Nuclear Information System (INIS)

    Ehmann, W.D.; Vance, D.

    1991-01-01

    This book provides both the fundamentals of radiochemistry as well as specific applications of nuclear techniques to analytical chemistry. It includes such areas of application as radioimmunoassay and activation techniques using very short-lined indicator radionuclides. It emphasizes the current nuclear methods of analysis such as neutron activation PIXE, nuclear reaction analysis, Rutherford backscattering, isotope dilution analysis and others

  8. Computational methods in power system analysis

    CERN Document Server

    Idema, Reijer

    2014-01-01

    This book treats state-of-the-art computational methods for power flow studies and contingency analysis. In the first part the authors present the relevant computational methods and mathematical concepts. In the second part, power flow and contingency analysis are treated. Furthermore, traditional methods to solve such problems are compared to modern solvers, developed using the knowledge of the first part of the book. Finally, these solvers are analyzed both theoretically and experimentally, clearly showing the benefits of the modern approach.

  9. Three-dimensional quantitative structure-activity relationship (3D QSAR) and pharmacophore elucidation of tetrahydropyran derivatives as serotonin and norepinephrine transporter inhibitors

    Science.gov (United States)

    Kharkar, Prashant S.; Reith, Maarten E. A.; Dutta, Aloke K.

    2008-01-01

    Three-dimensional quantitative structure-activity relationship (3D QSAR) using comparative molecular field analysis (CoMFA) was performed on a series of substituted tetrahydropyran (THP) derivatives possessing serotonin (SERT) and norepinephrine (NET) transporter inhibitory activities. The study aimed to rationalize the potency of these inhibitors for SERT and NET as well as the observed selectivity differences for NET over SERT. The dataset consisted of 29 molecules, of which 23 molecules were used as the training set for deriving CoMFA models for SERT and NET uptake inhibitory activities. Superimpositions were performed using atom-based fitting and 3-point pharmacophore-based alignment. Two charge calculation methods, Gasteiger-Hückel and semiempirical PM3, were tried. Both alignment methods were analyzed in terms of their predictive abilities and produced comparable results with high internal and external predictivities. The models obtained using the 3-point pharmacophore-based alignment outperformed the models with atom-based fitting in terms of relevant statistics and interpretability of the generated contour maps. Steric fields dominated electrostatic fields in terms of contribution. The selectivity analysis (NET over SERT), though yielded models with good internal predictivity, showed very poor external test set predictions. The analysis was repeated with 24 molecules after systematically excluding so-called outliers (5 out of 29) from the model derivation process. The resulting CoMFA model using the atom-based fitting exhibited good statistics and was able to explain most of the selectivity (NET over SERT)-discriminating factors. The presence of -OH substituent on the THP ring was found to be one of the most important factors governing the NET selectivity over SERT. Thus, a 4-point NET-selective pharmacophore, after introducing this newly found H-bond donor/acceptor feature in addition to the initial 3-point pharmacophore, was proposed.

  10. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

    Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

  11. Text analysis methods, text analysis apparatuses, and articles of manufacture

    Science.gov (United States)

    Whitney, Paul D; Willse, Alan R; Lopresti, Charles A; White, Amanda M

    2014-10-28

    Text analysis methods, text analysis apparatuses, and articles of manufacture are described according to some aspects. In one aspect, a text analysis method includes accessing information indicative of data content of a collection of text comprising a plurality of different topics, using a computing device, analyzing the information indicative of the data content, and using results of the analysis, identifying a presence of a new topic in the collection of text.

  12. Nuclear analysis methods. Rudiments of radiation protection

    International Nuclear Information System (INIS)

    Roth, E.

    1998-01-01

    The nuclear analysis methods are generally used to analyse radioactive elements but they can be used also for chemical analysis, with fields such analysis and characterization of traces. The principles of radiation protection are explained (ALARA), the biological effects of ionizing radiations are given, elements and units used in radiation protection are reminded in tables. A part of this article is devoted to how to use radiation protection in a nuclear analysis laboratory. (N.C.)

  13. 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.

  14. Considerations of nano-QSAR/QSPR models for nanopesticide risk assessment within the European legislative framework.

    Science.gov (United States)

    Villaverde, Juan José; Sevilla-Morán, Beatriz; López-Goti, Carmen; Alonso-Prados, José Luis; Sandín-España, Pilar

    2018-09-01

    The European market for pesticides is currently legislated through the well-developed Regulation (EC) No. 1107/2009. This regulation promotes the competitiveness of European agriculture, recognizing the necessity of safe pesticides for human and animal health and the environment to protect crops against pests, diseases and weeds. In this sense, nanotechnology can provide a tremendous opportunity to achieve a more rational use of pesticides. However, the lack of information regarding nanopesticides and their fate and behavior in the environment and their effects on human and animal health is inhibiting rapid nanopesticide incorporation into European Union agriculture. This review analyzes the recent state of knowledge on nanopesticide risk assessment, highlighting the challenges that need to be overcame to accelerate the arrival of these new tools for plant protection to European agricultural professionals. Novel nano-Quantitative Structure-Activity/Structure-Property Relationship (nano-QSAR/QSPR) tools for risk assessment are analyzed, including modeling methods and validation procedures towards the potential of these computational instruments to meet the current requirements for authorization of nanoformulations. Future trends on these issues, of pressing importance within the context of the current European pesticide legislative framework, are also discussed. Standard protocols to make high-quality and well-described datasets for the series of related but differently sized nanoparticles/nanopesticides are required. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Using quantitative structure-activity relationships (QSAR) to predict toxic endpoints for polycyclic aromatic hydrocarbons (PAH).

    Science.gov (United States)

    Bruce, Erica D; Autenrieth, Robin L; Burghardt, Robert C; Donnelly, K C; McDonald, Thomas J

    2008-01-01

    Quantitative structure-activity relationships (QSAR) offer a reliable, cost-effective alternative to the time, money, and animal lives necessary to determine chemical toxicity by traditional methods. Additionally, humans are exposed to tens of thousands of chemicals in their lifetimes, necessitating the determination of chemical toxicity and screening for those posing the greatest risk to human health. This study developed models to predict toxic endpoints for three bioassays specific to several stages of carcinogenesis. The ethoxyresorufin O-deethylase assay (EROD), the Salmonella/microsome assay, and a gap junction intercellular communication (GJIC) assay were chosen for their ability to measure toxic endpoints specific to activation-, induction-, and promotion-related effects of polycyclic aromatic hydrocarbons (PAH). Shape-electronic, spatial, information content, and topological descriptors proved to be important descriptors in predicting the toxicity of PAH in these bioassays. Bioassay-based toxic equivalency factors (TEF(B)) were developed for several PAH using the quantitative structure-toxicity relationships (QSTR) developed. Predicting toxicity for a specific PAH compound, such as a bioassay-based potential potency (PP(B)) or a TEF(B), is possible by combining the predicted behavior from the QSTR models. These toxicity estimates may then be incorporated into a risk assessment for compounds that lack toxicity data. Accurate toxicity predictions are made by examining each type of endpoint important to the process of carcinogenicity, and a clearer understanding between composition and toxicity can be obtained.

  16. 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.

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

    Science.gov (United States)

    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.

  18. 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.

  19. Short communication: cheminformatics analysis to identify predictors of antiviral drug penetration into the female genital tract.

    Science.gov (United States)

    Thompson, Corbin G; Sedykh, Alexander; Nicol, Melanie R; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Kashuba, Angela D M

    2014-11-01

    The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R(2)test=0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ≥1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

  20. 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.

  1. 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

  2. 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.

  3. Novel qsar combination forecast model for insect repellent coupling support vector regression and k-nearest-neighbor

    International Nuclear Information System (INIS)

    Wang, L.F.; Bai, L.Y.

    2013-01-01

    To improve the precision of quantitative structure-activity relationship (QSAR) modeling for aromatic carboxylic acid derivatives insect repellent, a novel nonlinear combination forecast model was proposed integrating support vector regression (SVR) and K-nearest neighbor (KNN): Firstly, search optimal kernel function and nonlinearly select molecular descriptors by the rule of minimum MSE value using SVR. Secondly, illuminate the effects of all descriptors on biological activity by multi-round enforcement resistance-selection. Thirdly, construct the sub-models with predicted values of different KNN. Then, get the optimal kernel and corresponding retained sub-models through subtle selection. Finally, make prediction with leave-one-out (LOO) method in the basis of reserved sub-models. Compared with previous widely used models, our work shows significant improvement in modeling performance, which demonstrates the superiority of the present combination forecast model. (author)

  4. Microlocal methods in the analysis of the boundary element method

    DEFF Research Database (Denmark)

    Pedersen, Michael

    1993-01-01

    The application of the boundary element method in numerical analysis is based upon the use of boundary integral operators stemming from multiple layer potentials. The regularity properties of these operators are vital in the development of boundary integral equations and error estimates. We show...

  5. Statistical methods for categorical data analysis

    CERN Document Server

    Powers, Daniel

    2008-01-01

    This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/

  6. Development of Ultraviolet Spectrophotometric Method for Analysis ...

    African Journals Online (AJOL)

    HP

    Method for Analysis of Lornoxicam in Solid Dosage. Forms. Sunit Kumar Sahoo ... testing. Mean recovery was 100.82 % for tablets. Low values of % RSD indicate .... Saharty E, Refaat YS, Khateeb ME. Stability-. Indicating. Spectrophotometric.

  7. 3D-QSAR and molecular docking studies on derivatives of MK-0457, GSK1070916 and SNS-314 as inhibitors against Aurora B kinase.

    Science.gov (United States)

    Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi

    2010-11-02

    Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.

  8. 3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

    Directory of Open Access Journals (Sweden)

    Chunzhi Ai

    2010-11-01

    Full Text Available Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA, comparative molecular similarity indices analysis (CoMSIA, homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q2 = 0.605, r2pred = 0.826, (q2 = 0.52, r2pred = 0.798 and (q2 = 0.582, r2pred = 0.971 for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.

  9. An introduction to numerical methods and analysis

    CERN Document Server

    Epperson, James F

    2013-01-01

    Praise for the First Edition "". . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises.""-Zentralblatt MATH "". . . carefully structured with many detailed worked examples.""-The Mathematical Gazette The Second Edition of the highly regarded An Introduction to Numerical Methods and Analysis provides a fully revised guide to numerical approximation. The book continues to be accessible and expertly guides readers through the many available techniques of numerical methods and analysis. An Introduction to

  10. 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.

  11. 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)

  12. Hypothesis analysis methods, hypothesis analysis devices, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio P [Richland, WA; Cowell, Andrew J [Kennewick, WA; Gregory, Michelle L [Richland, WA; Baddeley, Robert L [Richland, WA; Paulson, Patrick R [Pasco, WA; Tratz, Stephen C [Richland, WA; Hohimer, Ryan E [West Richland, WA

    2012-03-20

    Hypothesis analysis methods, hypothesis analysis devices, and articles of manufacture are described according to some aspects. In one aspect, a hypothesis analysis method includes providing a hypothesis, providing an indicator which at least one of supports and refutes the hypothesis, using the indicator, associating evidence with the hypothesis, weighting the association of the evidence with the hypothesis, and using the weighting, providing information regarding the accuracy of the hypothesis.

  13. Relating Actor Analysis Methods to Policy Problems

    NARCIS (Netherlands)

    Van der Lei, T.E.

    2009-01-01

    For a policy analyst the policy problem is the starting point for the policy analysis process. During this process the policy analyst structures the policy problem and makes a choice for an appropriate set of methods or techniques to analyze the problem (Goeller 1984). The methods of the policy

  14. 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.

  15. Nodal method for fast reactor analysis

    International Nuclear Information System (INIS)

    Shober, R.A.

    1979-01-01

    In this paper, a nodal method applicable to fast reactor diffusion theory analysis has been developed. This method has been shown to be accurate and efficient in comparison to highly optimized finite difference techniques. The use of an analytic solution to the diffusion equation as a means of determining accurate coupling relationships between nodes has been shown to be highly accurate and efficient in specific two-group applications, as well as in the current multigroup method

  16. Inelastic analysis methods for piping systems

    International Nuclear Information System (INIS)

    Boyle, J.T.; Spence, J.

    1980-01-01

    The analysis of pipework systems which operate in an environment where local inelastic strains are evident is one of the most demanding problems facing the stress analyst in the nuclear field. The spatial complexity of even the most modest system makes a detailed analysis using finite element techniques beyond the scope of current computer technology. For this reason the emphasis has been on simplified methods. It is the aim of this paper to provide a reasonably complete, state-of-the-art review of inelastic pipework analysis methods and to attempt to highlight areas where reliable information is lacking and further work is needed. (orig.)

  17. Excitation methods for energy dispersive analysis

    International Nuclear Information System (INIS)

    Jaklevic, J.M.

    1976-01-01

    The rapid development in recent years of energy dispersive x-ray fluorescence analysis has been based primarily on improvements in semiconductor detector x-ray spectrometers. However, the whole analysis system performance is critically dependent on the availability of optimum methods of excitation for the characteristic x rays in specimens. A number of analysis facilities based on various methods of excitation have been developed over the past few years. A discussion is given of the features of various excitation methods including charged particles, monochromatic photons, and broad-energy band photons. The effects of the excitation method on background and sensitivity are discussed from both theoretical and experimental viewpoints. Recent developments such as pulsed excitation and polarized photons are also discussed

  18. A strategy for evaluating pathway analysis methods.

    Science.gov (United States)

    Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques

    2017-10-13

    Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth

  19. Instrumental methods of analysis, 7th edition

    International Nuclear Information System (INIS)

    Willard, H.H.; Merritt, L.L. Jr.; Dean, J.A.; Settle, F.A. Jr.

    1988-01-01

    The authors have prepared an organized and generally polished product. The book is fashioned to be used as a textbook for an undergraduate instrumental analysis course, a supporting textbook for graduate-level courses, and a general reference work on analytical instrumentation and techniques for professional chemists. Four major areas are emphasized: data collection and processing, spectroscopic instrumentation and methods, liquid and gas chromatographic methods, and electrochemical methods. Analytical instrumentation and methods have been updated, and a thorough citation of pertinent recent literature is included

  20. Limitations of systemic accident analysis methods

    Directory of Open Access Journals (Sweden)

    Casandra Venera BALAN

    2016-12-01

    Full Text Available In terms of system theory, the description of complex accidents is not limited to the analysis of the sequence of events / individual conditions, but highlights nonlinear functional characteristics and frames human or technical performance in relation to normal functioning of the system, in safety conditions. Thus, the research of the system entities as a whole is no longer an abstraction of a concrete situation, but an exceeding of the theoretical limits set by analysis based on linear methods. Despite the issues outlined above, the hypothesis that there isn’t a complete method for accident analysis is supported by the nonlinearity of the considered function or restrictions, imposing a broad vision of the elements introduced in the analysis, so it can identify elements corresponding to nominal parameters or trigger factors.

  1. Application of Software Safety Analysis Methods

    International Nuclear Information System (INIS)

    Park, G. Y.; Hur, S.; Cheon, S. W.; Kim, D. H.; Lee, D. Y.; Kwon, K. C.; Lee, S. J.; Koo, Y. H.

    2009-01-01

    A fully digitalized reactor protection system, which is called the IDiPS-RPS, was developed through the KNICS project. The IDiPS-RPS has four redundant and separated channels. Each channel is mainly composed of a group of bistable processors which redundantly compare process variables with their corresponding setpoints and a group of coincidence processors that generate a final trip signal when a trip condition is satisfied. Each channel also contains a test processor called the ATIP and a display and command processor called the COM. All the functions were implemented in software. During the development of the safety software, various software safety analysis methods were applied, in parallel to the verification and validation (V and V) activities, along the software development life cycle. The software safety analysis methods employed were the software hazard and operability (Software HAZOP) study, the software fault tree analysis (Software FTA), and the software failure modes and effects analysis (Software FMEA)

  2. Spatial analysis statistics, visualization, and computational methods

    CERN Document Server

    Oyana, Tonny J

    2015-01-01

    An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...

  3. Advanced analysis methods in particle physics

    Energy Technology Data Exchange (ETDEWEB)

    Bhat, Pushpalatha C.; /Fermilab

    2010-10-01

    Each generation of high energy physics experiments is grander in scale than the previous - more powerful, more complex and more demanding in terms of data handling and analysis. The spectacular performance of the Tevatron and the beginning of operations of the Large Hadron Collider, have placed us at the threshold of a new era in particle physics. The discovery of the Higgs boson or another agent of electroweak symmetry breaking and evidence of new physics may be just around the corner. The greatest challenge in these pursuits is to extract the extremely rare signals, if any, from huge backgrounds arising from known physics processes. The use of advanced analysis techniques is crucial in achieving this goal. In this review, I discuss the concepts of optimal analysis, some important advanced analysis methods and a few examples. The judicious use of these advanced methods should enable new discoveries and produce results with better precision, robustness and clarity.

  4. Review of strain buckling: analysis methods

    International Nuclear Information System (INIS)

    Moulin, D.

    1987-01-01

    This report represents an attempt to review the mechanical analysis methods reported in the literature to account for the specific behaviour that we call buckling under strain. In this report, this expression covers all buckling mechanisms in which the strains imposed play a role, whether they act alone (as in simple buckling under controlled strain), or whether they act with other loadings (primary loading, such as pressure, for example). Attention is focused on the practical problems relevant to LMFBR reactors. The components concerned are distinguished by their high slenderness ratios and by rather high thermal levels, both constant and variable with time. Conventional static buckling analysis methods are not always appropriate for the consideration of buckling under strain. New methods must therefore be developed in certain cases. It is also hoped that this review will facilitate the coding of these analytical methods to aid the constructor in his design task and to identify the areas which merit further investigation

  5. Analysis of mixed data methods & applications

    CERN Document Server

    de Leon, Alexander R

    2013-01-01

    A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and seamless transitions between chaptersAll chapters follow a common structure, with an introduction and a concluding summary, and include illustrative examples from real-life case studies in developmental toxicolog

  6. Scope-Based Method Cache Analysis

    DEFF Research Database (Denmark)

    Huber, Benedikt; Hepp, Stefan; Schoeberl, Martin

    2014-01-01

    The quest for time-predictable systems has led to the exploration of new hardware architectures that simplify analysis and reasoning in the temporal domain, while still providing competitive performance. For the instruction memory, the method cache is a conceptually attractive solution, as it req......The quest for time-predictable systems has led to the exploration of new hardware architectures that simplify analysis and reasoning in the temporal domain, while still providing competitive performance. For the instruction memory, the method cache is a conceptually attractive solution...

  7. 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

  8. 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...

  9. 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

  10. 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...

  11. 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.

  12. 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.

  13. Quantitative analysis method for ship construction quality

    Directory of Open Access Journals (Sweden)

    FU Senzong

    2017-03-01

    Full Text Available The excellent performance of a ship is assured by the accurate evaluation of its construction quality. For a long time, research into the construction quality of ships has mainly focused on qualitative analysis due to a shortage of process data, which results from limited samples, varied process types and non-standardized processes. Aiming at predicting and controlling the influence of the construction process on the construction quality of ships, this article proposes a reliability quantitative analysis flow path for the ship construction process and fuzzy calculation method. Based on the process-quality factor model proposed by the Function-Oriented Quality Control (FOQC method, we combine fuzzy mathematics with the expert grading method to deduce formulations calculating the fuzzy process reliability of the ordinal connection model, series connection model and mixed connection model. The quantitative analysis method is applied in analyzing the process reliability of a ship's shaft gear box installation, which proves the applicability and effectiveness of the method. The analysis results can be a useful reference for setting key quality inspection points and optimizing key processes.

  14. Piping dynamic analysis by the synthesis method

    International Nuclear Information System (INIS)

    Bezler, P.; Curreri, J.R.

    1976-01-01

    Since piping systems are a frequent source of noise and vibrations, their efficient dynamic analysis is imperative. As an alternate to more conventional analyses methods, an application of the synthesis method to piping vibrations analyses is demonstrated. Specifically, the technique is illustrated by determining the normal modes and natural frequencies of a composite bend from the normal mode and natural frequency data of two component parts. A comparison of the results to those derived for the composite bend by other techniques is made

  15. Probabilistic Analysis Methods for Hybrid Ventilation

    DEFF Research Database (Denmark)

    Brohus, Henrik; Frier, Christian; Heiselberg, Per

    This paper discusses a general approach for the application of probabilistic analysis methods in the design of ventilation systems. The aims and scope of probabilistic versus deterministic methods are addressed with special emphasis on hybrid ventilation systems. A preliminary application...... of stochastic differential equations is presented comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions....

  16. Chemical analysis by nuclear methods. v. 2

    International Nuclear Information System (INIS)

    Alfassi, Z.B.

    1998-01-01

    'Chemical analysis by Nuclear Methods' is an effort of some renowned authors in field of nuclear chemistry and radiochemistry which is compiled by Alfassi, Z.B. and translated into Farsi version collected in two volumes. The second volume consists of the following chapters: Detecting ion recoil scattering and elastic scattering are dealt in the eleventh chapter, the twelfth chapter is devoted to nuclear reaction analysis using charged particles, X-ray emission is discussed at thirteenth chapter, the fourteenth chapter is about using ion microprobes, X-ray fluorescence analysis is discussed in the fifteenth chapter, alpha, beta and gamma ray scattering in chemical analysis are dealt in chapter sixteen, Moessbauer spectroscopy and positron annihilation are discussed in chapter seventeen and eighteen; The last two chapters are about isotope dilution analysis and radioimmunoassay

  17. Numerical methods in software and analysis

    CERN Document Server

    Rice, John R

    1992-01-01

    Numerical Methods, Software, and Analysis, Second Edition introduces science and engineering students to the methods, tools, and ideas of numerical computation. Introductory courses in numerical methods face a fundamental problem-there is too little time to learn too much. This text solves that problem by using high-quality mathematical software. In fact, the objective of the text is to present scientific problem solving using standard mathematical software. This book discusses numerous programs and software packages focusing on the IMSL library (including the PROTRAN system) and ACM Algorithm

  18. 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.

  19. Nonlinear structural analysis using integrated force method

    Indian Academy of Sciences (India)

    A new formulation termed the Integrated Force Method (IFM) was proposed by Patnaik ... nated ``Structure (nY m)'' where (nY m) are the force and displacement degrees of ..... Patnaik S N, Yadagiri S 1976 Frequency analysis of structures.

  20. Modern methods of wine quality analysis

    Directory of Open Access Journals (Sweden)

    Галина Зуфарівна Гайда

    2015-06-01

    Full Text Available  In this paper physical-chemical and enzymatic methods of quantitative analysis of the basic wine components were reviewed. The results of own experiments were presented for the development of enzyme- and cell-based amperometric sensors on ethanol, lactate, glucose, arginine

  1. Multiple predictor smoothing methods for sensitivity analysis

    International Nuclear Information System (INIS)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-01-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

  2. Economic analysis of alternative LLW disposal methods

    International Nuclear Information System (INIS)

    Foutes, C.E.

    1987-01-01

    The Environmental Protection Agency (EPA) has evaluated the costs and benefits of alternative disposal technologies as part of its program to develop generally applicable environmental standards for the land disposal of low-level radioactive waste (LLW). Costs, population health effects and Critical Population Group (CPG) exposures resulting from alternative waste treatment and disposal methods were developed and input into the analysis. The cost-effectiveness analysis took into account a number of waste streams, hydrogeologic and climatic region settings, and waste treatment and disposal methods. Total costs of each level of a standard included costs for packaging, processing, transportation, and burial of waste. Benefits are defined in terms of reductions in the general population health risk (expected fatal cancers and genetic effects) evaluated over 10,000 years. A cost-effectiveness ratio, was calculated for each alternative standard. This paper describes the alternatives considered and preliminary results of the cost-effectiveness analysis

  3. Reliability and risk analysis methods research plan

    International Nuclear Information System (INIS)

    1984-10-01

    This document presents a plan for reliability and risk analysis methods research to be performed mainly by the Reactor Risk Branch (RRB), Division of Risk Analysis and Operations (DRAO), Office of Nuclear Regulatory Research. It includes those activities of other DRAO branches which are very closely related to those of the RRB. Related or interfacing programs of other divisions, offices and organizations are merely indicated. The primary use of this document is envisioned as an NRC working document, covering about a 3-year period, to foster better coordination in reliability and risk analysis methods development between the offices of Nuclear Regulatory Research and Nuclear Reactor Regulation. It will also serve as an information source for contractors and others to more clearly understand the objectives, needs, programmatic activities and interfaces together with the overall logical structure of the program

  4. Multiple predictor smoothing methods for sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-08-01

    The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.

  5. Spectroscopic Chemical Analysis Methods and Apparatus

    Science.gov (United States)

    Hug, William F. (Inventor); Reid, Ray D. (Inventor); Bhartia, Rohit (Inventor); Lane, Arthur L. (Inventor)

    2018-01-01

    Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted along with photoluminescence spectroscopy (i.e. fluorescence and/or phosphorescence spectroscopy) to provide high levels of sensitivity and specificity in the same instrument.

  6. Computational methods for nuclear criticality safety analysis

    International Nuclear Information System (INIS)

    Maragni, M.G.

    1992-01-01

    Nuclear criticality safety analyses require the utilization of methods which have been tested and verified against benchmarks results. In this work, criticality calculations based on the KENO-IV and MCNP codes are studied aiming the qualification of these methods at the IPEN-CNEN/SP and COPESP. The utilization of variance reduction techniques is important to reduce the computer execution time, and several of them are analysed. As practical example of the above methods, a criticality safety analysis for the storage tubes for irradiated fuel elements from the IEA-R1 research has been carried out. This analysis showed that the MCNP code is more adequate for problems with complex geometries, and the KENO-IV code shows conservative results when it is not used the generalized geometry option. (author)

  7. 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.

  8. PIXE - a new method for elemental analysis

    International Nuclear Information System (INIS)

    Johansson, S.A.E.

    1983-01-01

    With elemental analysis we mean the determination of which chemical elements are present in a sample and of their concentration. This is an old and important problem in chemistry. The earliest methods were purely chemical and many such methods are still used. However, various methods based on physical principles have gradually become more and more important. One such method is neutron activation. When the sample is bombarded with neutrons it becomes radioactive and the various radioactive isotopes produced can be identified by the radiation they emit. From the measured intensity of the radiation one can calculate how much of a certain element that is present in the sample. Another possibility is to study the light emitted when the sample is excited in various ways. A spectroscopic investigation of the light can identify the chemical elements and allows also a determination of their concentration in the sample. In the same way, if a sample can be brought to emit X-rays, this radiation is also characteristic for the elements present and can be used to determine the elemental concentration. One such X-ray method which has been developed recently is PIXE. The name is an acronym for Particle Induced X-ray Emission and indicates the principle of the method. Particles in this context means heavy, charged particles such as protons and a-particles of rather high energy. Hence, in PIXE-analysis the sample is irradiated in the beam of an accelerator and the emitted X-rays are studied. (author)

  9. Dependability Analysis Methods For Configurable Software

    International Nuclear Information System (INIS)

    Dahll, Gustav; Pulkkinen, Urho

    1996-01-01

    Configurable software systems are systems which are built up by standard software components in the same way as a hardware system is built up by standard hardware components. Such systems are often used in the control of NPPs, also in safety related applications. A reliability analysis of such systems is therefore necessary. This report discusses what configurable software is, and what is particular with respect to reliability assessment of such software. Two very commonly used techniques in traditional reliability analysis, viz. failure mode, effect and criticality analysis (FMECA) and fault tree analysis are investigated. A real example is used to illustrate the discussed methods. Various aspects relevant to the assessment of the software reliability in such systems are discussed. Finally some models for quantitative software reliability assessment applicable on configurable software systems are described. (author)

  10. Cask crush pad analysis using detailed and simplified analysis methods

    International Nuclear Information System (INIS)

    Uldrich, E.D.; Hawkes, B.D.

    1997-01-01

    A crush pad has been designed and analyzed to absorb the kinetic energy of a hypothetically dropped spent nuclear fuel shipping cask into a 44-ft. deep cask unloading pool at the Fluorinel and Storage Facility (FAST). This facility, located at the Idaho Chemical Processing Plant (ICPP) at the Idaho national Engineering and Environmental Laboratory (INEEL), is a US Department of Energy site. The basis for this study is an analysis by Uldrich and Hawkes. The purpose of this analysis was to evaluate various hypothetical cask drop orientations to ensure that the crush pad design was adequate and the cask deceleration at impact was less than 100 g. It is demonstrated herein that a large spent fuel shipping cask, when dropped onto a foam crush pad, can be analyzed by either hand methods or by sophisticated dynamic finite element analysis using computer codes such as ABAQUS. Results from the two methods are compared to evaluate accuracy of the simplified hand analysis approach

  11. Advanced Analysis Methods in High Energy Physics

    Energy Technology Data Exchange (ETDEWEB)

    Pushpalatha C. Bhat

    2001-10-03

    During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

  12. Spatial Analysis Methods of Road Traffic Collisions

    DEFF Research Database (Denmark)

    Loo, Becky P. Y.; Anderson, Tessa Kate

    Spatial Analysis Methods of Road Traffic Collisions centers on the geographical nature of road crashes, and uses spatial methods to provide a greater understanding of the patterns and processes that cause them. Written by internationally known experts in the field of transport geography, the book...... outlines the key issues in identifying hazardous road locations (HRLs), considers current approaches used for reducing and preventing road traffic collisions, and outlines a strategy for improved road safety. The book covers spatial accuracy, validation, and other statistical issues, as well as link...

  13. Simple gas chromatographic method for furfural analysis.

    Science.gov (United States)

    Gaspar, Elvira M S M; Lopes, João F

    2009-04-03

    A new, simple, gas chromatographic method was developed for the direct analysis of 5-hydroxymethylfurfural (5-HMF), 2-furfural (2-F) and 5-methylfurfural (5-MF) in liquid and water soluble foods, using direct immersion SPME coupled to GC-FID and/or GC-TOF-MS. The fiber (DVB/CAR/PDMS) conditions were optimized: pH effect, temperature, adsorption and desorption times. The method is simple and accurate (RSDfurfurals will contribute to characterise and quantify their presence in the human diet.

  14. Neutron activation analysis: principle and methods

    International Nuclear Information System (INIS)

    Reddy, A.V.R.; Acharya, R.

    2006-01-01

    Neutron activation analysis (NAA) is a powerful isotope specific nuclear analytical technique for simultaneous determination of elemental composition of major, minor and trace elements in diverse matrices. The technique is capable of yielding high analytical sensitivity and low detection limits (ppm to ppb). Due to high penetration power of neutrons and gamma rays, NAA experiences negligible matrix effects in the samples of different origins. Depending on the sample matrix and element of interest NAA technique is used non-destructively, known as instrumental neutron activation analysis (INAA), or through chemical NAA methods. The present article describes principle of NAA, different methods and gives a overview some applications in the fields like environment, biology, geology, material sciences, nuclear technology and forensic sciences. (author)

  15. Digital dream analysis: a revised method.

    Science.gov (United States)

    Bulkeley, Kelly

    2014-10-01

    This article demonstrates the use of a digital word search method designed to provide greater accuracy, objectivity, and speed in the study of dreams. A revised template of 40 word search categories, built into the website of the Sleep and Dream Database (SDDb), is applied to four "classic" sets of dreams: The male and female "Norm" dreams of Hall and Van de Castle (1966), the "Engine Man" dreams discussed by Hobson (1988), and the "Barb Sanders Baseline 250" dreams examined by Domhoff (2003). A word search analysis of these original dream reports shows that a digital approach can accurately identify many of the same distinctive patterns of content found by previous investigators using much more laborious and time-consuming methods. The results of this study emphasize the compatibility of word search technologies with traditional approaches to dream content analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Numerical methods and analysis of multiscale problems

    CERN Document Server

    Madureira, Alexandre L

    2017-01-01

    This book is about numerical modeling of multiscale problems, and introduces several asymptotic analysis and numerical techniques which are necessary for a proper approximation of equations that depend on different physical scales. Aimed at advanced undergraduate and graduate students in mathematics, engineering and physics – or researchers seeking a no-nonsense approach –, it discusses examples in their simplest possible settings, removing mathematical hurdles that might hinder a clear understanding of the methods. The problems considered are given by singular perturbed reaction advection diffusion equations in one and two-dimensional domains, partial differential equations in domains with rough boundaries, and equations with oscillatory coefficients. This work shows how asymptotic analysis can be used to develop and analyze models and numerical methods that are robust and work well for a wide range of parameters.

  17. Qualitative data analysis a methods sourcebook

    CERN Document Server

    Miles, Matthew B; Saldana, Johnny

    2014-01-01

    The Third Edition of Miles & Huberman's classic research methods text is updated and streamlined by Johnny SaldaNa, author of The Coding Manual for Qualitative Researchers. Several of the data display strategies from previous editions are now presented in re-envisioned and reorganized formats to enhance reader accessibility and comprehension. The Third Edition's presentation of the fundamentals of research design and data management is followed by five distinct methods of analysis: exploring, describing, ordering, explaining, and predicting. Miles and Huberman's original research studies are profiled and accompanied with new examples from SaldaNa's recent qualitative work. The book's most celebrated chapter, "Drawing and Verifying Conclusions," is retained and revised, and the chapter on report writing has been greatly expanded, and is now called "Writing About Qualitative Research." Comprehensive and authoritative, Qualitative Data Analysis has been elegantly revised for a new generation of qualitative r...

  18. An exergy method for compressor performance analysis

    Energy Technology Data Exchange (ETDEWEB)

    McGovern, J A; Harte, S [Trinity Coll., Dublin (Ireland)

    1995-07-01

    An exergy method for compressor performance analysis is presented. The purpose of this is to identify and quantify defects in the use of a compressor`s shaft power. This information can be used as the basis for compressor design improvements. The defects are attributed to friction, irreversible heat transfer, fluid throttling, and irreversible fluid mixing. They are described, on a common basis, as exergy destruction rates and their locations are identified. The method can be used with any type of positive displacement compressor. It is most readily applied where a detailed computer simulation program is available for the compressor. An analysis of an open reciprocating refrigeration compressor that used R12 refrigerant is given as an example. The results that are presented consist of graphs of the instantaneous rates of exergy destruction according to the mechanisms involved, a pie chart of the breakdown of the average shaft power wastage by mechanism, and a pie chart with a breakdown by location. (author)

  19. Methods for genetic linkage analysis using trisomies.

    OpenAIRE

    Feingold, E; Lamb, N E; Sherman, S L

    1995-01-01

    Certain genetic disorders are rare in the general population, but more common in individuals with specific trisomies. Examples of this include leukemia and duodenal atresia in trisomy 21. This paper presents a linkage analysis method for using trisomic individuals to map genes for such traits. It is based on a very general gene-specific dosage model that posits that the trait is caused by specific effects of different alleles at one or a few loci and that duplicate copies of "susceptibility" ...

  20. Machine Learning Methods for Production Cases Analysis

    Science.gov (United States)

    Mokrova, Nataliya V.; Mokrov, Alexander M.; Safonova, Alexandra V.; Vishnyakov, Igor V.

    2018-03-01

    Approach to analysis of events occurring during the production process were proposed. Described machine learning system is able to solve classification tasks related to production control and hazard identification at an early stage. Descriptors of the internal production network data were used for training and testing of applied models. k-Nearest Neighbors and Random forest methods were used to illustrate and analyze proposed solution. The quality of the developed classifiers was estimated using standard statistical metrics, such as precision, recall and accuracy.

  1. Safety relief valve alternate analysis method

    International Nuclear Information System (INIS)

    Adams, R.H.; Javid, A.; Khatua, T.P.

    1981-01-01

    An experimental test program was started in the United States in 1976 to define and quantify Safety Relief Valve (SRV) phenomena in General Electric Mark I Suppression Chambers. The testing considered several discharged devices and was used to correlate SRV load prediction models. The program was funded by utilities with Mark I containments and has resulted in a detailed SRV load definition as a portion of the Mark I containment program Load Definition Report (LDR). The (USNRC) has reviewed and approved the LDR SRV load definition. In addition, the USNRC has permitted calibration of structural models used for predicting torus response to SRV loads. Model calibration is subject to confirmatory in-plant testing. The SRV methodology given in the LDR requires that transient dynamic pressures be applied to a torus structural model that includes a fluid added mass matrix. Preliminary evaluations of torus response have indicated order of magnitude conservatisms, with respect to test results, which could result in unrealistic containment modifications. In addition, structural response trends observed in full-scale tests between cold pipe, first valve actuation and hot pipe, subsequent valve actuation conditions have not been duplicated using current analysis methods. It was suggested by others that an energy approach using current fluid models be utilized to define loads. An alternate SRV analysis method is defined to correct suppression chamber structural response to a level that permits economical but conservative design. Simple analogs are developed for the purpose of correcting the analytical response obtained from LDR analysis methods. Analogs evaluated considered forced vibration and free vibration structural response. The corrected response correlated well with in-plant test response. The correlation of the analytical model at test conditions permits application of the alternate analysis method at design conditions. (orig./HP)

  2. Analysis and comparison of biometric methods

    OpenAIRE

    Zatloukal, Filip

    2011-01-01

    The thesis deals with biometrics and biometric systems and the possibility to use these systems in the enterprise. Aim of this study is an analysis and description of selected types of biometric identification methods and their advantages and shortcomings. The work is divided into two parts. The first part is theoretical, describes the basic concepts of biometrics, biometric identification criteria, currently used identification systems, the ways of biometric systems use, performance measurem...

  3. Statistical trend analysis methods for temporal phenomena

    International Nuclear Information System (INIS)

    Lehtinen, E.; Pulkkinen, U.; Poern, K.

    1997-04-01

    We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods

  4. Statistical trend analysis methods for temporal phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)

    1997-04-01

    We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.

  5. Analysis Method for Integrating Components of Product

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Jun Ho [Inzest Co. Ltd, Seoul (Korea, Republic of); Lee, Kun Sang [Kookmin Univ., Seoul (Korea, Republic of)

    2017-04-15

    This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

  6. Analysis Method for Integrating Components of Product

    International Nuclear Information System (INIS)

    Choi, Jun Ho; Lee, Kun Sang

    2017-01-01

    This paper presents some of the methods used to incorporate the parts constituting a product. A new relation function concept and its structure are introduced to analyze the relationships of component parts. This relation function has three types of information, which can be used to establish a relation function structure. The relation function structure of the analysis criteria was established to analyze and present the data. The priority components determined by the analysis criteria can be integrated. The analysis criteria were divided based on their number and orientation, as well as their direct or indirect characteristic feature. This paper presents a design algorithm for component integration. This algorithm was applied to actual products, and the components inside the product were integrated. Therefore, the proposed algorithm was used to conduct research to improve the brake discs for bicycles. As a result, an improved product similar to the related function structure was actually created.

  7. Probabilistic methods in fire-risk analysis

    International Nuclear Information System (INIS)

    Brandyberry, M.D.

    1989-01-01

    The first part of this work outlines a method for assessing the frequency of ignition of a consumer product in a building and shows how the method would be used in an example scenario utilizing upholstered furniture as the product and radiant auxiliary heating devices (electric heaters, wood stoves) as the ignition source. Deterministic thermal models of the heat-transport processes are coupled with parameter uncertainty analysis of the models and with a probabilistic analysis of the events involved in a typical scenario. This leads to a distribution for the frequency of ignition for the product. In second part, fire-risk analysis as currently used in nuclear plants is outlines along with a discussion of the relevant uncertainties. The use of the computer code COMPBRN is discussed for use in the fire-growth analysis along with the use of response-surface methodology to quantify uncertainties in the code's use. Generalized response surfaces are developed for temperature versus time for a cable tray, as well as a surface for the hot gas layer temperature and depth for a room of arbitrary geometry within a typical nuclear power plant compartment. These surfaces are then used to simulate the cable tray damage time in a compartment fire experiment

  8. 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.

  9. QSAR, docking and ADMET studies of artemisinin derivatives for antimalarial activity targeting plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

    Science.gov (United States)

    Qidwai, Tabish; Yadav, Dharmendra K; Khan, Feroz; Dhawan, Sangeeta; Bhakuni, R S

    2012-01-01

    This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64 possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported antimalarial activity. The correlation in terms of regression coefficient (r(2)) was 0.90 and prediction accuracy of model in terms of cross validation regression coefficient (rCV(2)) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24, A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.

  10. An unconventional method of quantitative microstructural analysis

    International Nuclear Information System (INIS)

    Rastani, M.

    1995-01-01

    The experiment described here introduces a simple methodology which could be used to replace the time-consuming and expensive conventional methods of metallographic and quantitative analysis of thermal treatment effect on microstructure. The method is ideal for the microstructural evaluation of tungsten filaments and other wire samples such as copper wire which can be conveniently coiled. Ten such samples were heat treated by ohmic resistance at temperatures which were expected to span the recrystallization range. After treatment, the samples were evaluated in the elastic recovery test. The normalized elastic recovery factor was defined in terms of these deflections. Experimentally it has shown that elastic recovery factor depends on the degree of recrystallization. In other words this factor is used to determine the fraction of unrecrystallized material. Because the elastic recovery method examines the whole filament rather than just one section through the filament as in metallographical method, it more accurately measures the degree of recrystallization. The method also takes a considerably shorter time and cost compared to the conventional method

  11. Homotopy analysis method for neutron diffusion calculations

    International Nuclear Information System (INIS)

    Cavdar, S.

    2009-01-01

    The Homotopy Analysis Method (HAM), proposed in 1992 by Shi Jun Liao and has been developed since then, is based on a fundamental concept in differential geometry and topology, the homotopy. It has proved useful for problems involving algebraic, linear/non-linear, ordinary/partial differential and differential-integral equations being an analytic, recursive method that provides a series sum solution. It has the advantage of offering a certain freedom for the choice of its arguments such as the initial guess, the auxiliary linear operator and the convergence control parameter, and it allows us to effectively control the rate and region of convergence of the series solution. HAM is applied for the fixed source neutron diffusion equation in this work, which is a part of our research motivated by the question of whether methods for solving the neutron diffusion equation that yield straightforward expressions but able to provide a solution of reasonable accuracy exist such that we could avoid analytic methods that are widely used but either fail to solve the problem or provide solutions through many intricate expressions that are likely to contain mistakes or numerical methods that require powerful computational resources and advanced programming skills due to their very nature or intricate mathematical fundamentals. Fourier basis are employed for expressing the initial guess due to the structure of the problem and its boundary conditions. We present the results in comparison with other widely used methods of Adomian Decomposition and Variable Separation.

  12. Detector Simulation: Data Treatment and Analysis Methods

    CERN Document Server

    Apostolakis, J

    2011-01-01

    Detector Simulation in 'Data Treatment and Analysis Methods', part of 'Landolt-Börnstein - Group I Elementary Particles, Nuclei and Atoms: Numerical Data and Functional Relationships in Science and Technology, Volume 21B1: Detectors for Particles and Radiation. Part 1: Principles and Methods'. This document is part of Part 1 'Principles and Methods' of Subvolume B 'Detectors for Particles and Radiation' of Volume 21 'Elementary Particles' of Landolt-Börnstein - Group I 'Elementary Particles, Nuclei and Atoms'. It contains the Section '4.1 Detector Simulation' of Chapter '4 Data Treatment and Analysis Methods' with the content: 4.1 Detector Simulation 4.1.1 Overview of simulation 4.1.1.1 Uses of detector simulation 4.1.2 Stages and types of simulation 4.1.2.1 Tools for event generation and detector simulation 4.1.2.2 Level of simulation and computation time 4.1.2.3 Radiation effects and background studies 4.1.3 Components of detector simulation 4.1.3.1 Geometry modeling 4.1.3.2 External fields 4.1.3.3 Intro...

  13. Data Analysis Methods for Library Marketing

    Science.gov (United States)

    Minami, Toshiro; Kim, Eunja

    Our society is rapidly changing to information society, where the needs and requests of the people on information access are different widely from person to person. Library's mission is to provide its users, or patrons, with the most appropriate information. Libraries have to know the profiles of their patrons, in order to achieve such a role. The aim of library marketing is to develop methods based on the library data, such as circulation records, book catalogs, book-usage data, and others. In this paper we discuss the methodology and imporatnce of library marketing at the beginning. Then we demonstrate its usefulness through some examples of analysis methods applied to the circulation records in Kyushu University and Guacheon Library, and some implication that obtained as the results of these methods. Our research is a big beginning towards the future when library marketing is an unavoidable tool.

  14. Phosphorus analysis in milk samples by neutron activation analysis method

    International Nuclear Information System (INIS)

    Oliveira, R.M. de; Cunha, I.I.L.

    1991-01-01

    The determination of phosphorus in milk samples by instrumental thermal neutron activation analysis is described. The procedure involves a short irradiation in a nuclear reactor and measurement of the beta radiation emitted by phosphorus - 32 after a suitable decay period. The sources of error were studied and the established method was applied to standard reference materials of known phosphorus content. (author)

  15. Methods of charged-particle activation analysis

    International Nuclear Information System (INIS)

    Chaudhri, M. Anwar; Chaudhri, M. Nasir; Jabbar, Q.; Nadeem, Q.

    2006-01-01

    The accuracy of Chaudhri's method for charged-particle activation analysis published in J. Radioanal. Chem. (1977) v. 37 p. 243 has been further demonstrated by extensive calculations. The nuclear reactions 12 C(d,n) 13 N, 63 Cu( 3 He,p) 65 Zn, 107 Ag(α,n) 110 In and 208 Pb(d,p) 209 Pb, the cross sections of which were easily available, have been examined for the detection of 12 C, 63 Cu, 107 Ag and 208 Pb, respectively, in matrices of Cu, Zr and Pb, at the bombarding energies of 4 - 22 MeV. The 'standard' is assumed to be in a carbon matrix. It has been clearly demonstrated that Chaudhri's method, which makes the charged particle activation analysis as simple as neutron activation analysis, provides results which are almost identical to, or only about 1-2 % different, from the results obtained using the full 'Activity Equation' involving solving complex integrals. It is valid even when the difference in the average atomic weights of matrices of the standard and the sample is large. (author)

  16. Development and analysis of finite volume methods

    International Nuclear Information System (INIS)

    Omnes, P.

    2010-05-01

    This document is a synthesis of a set of works concerning the development and the analysis of finite volume methods used for the numerical approximation of partial differential equations (PDEs) stemming from physics. In the first part, the document deals with co-localized Godunov type schemes for the Maxwell and wave equations, with a study on the loss of precision of this scheme at low Mach number. In the second part, discrete differential operators are built on fairly general, in particular very distorted or nonconforming, bidimensional meshes. These operators are used to approach the solutions of PDEs modelling diffusion, electro and magneto-statics and electromagnetism by the discrete duality finite volume method (DDFV) on staggered meshes. The third part presents the numerical analysis and some a priori as well as a posteriori error estimations for the discretization of the Laplace equation by the DDFV scheme. The last part is devoted to the order of convergence in the L2 norm of the finite volume approximation of the solution of the Laplace equation in one dimension and on meshes with orthogonality properties in two dimensions. Necessary and sufficient conditions, relatively to the mesh geometry and to the regularity of the data, are provided that ensure the second-order convergence of the method. (author)

  17. Creep analysis by the path function method

    International Nuclear Information System (INIS)

    Akin, J.E.; Pardue, R.M.

    1977-01-01

    The finite element method has become a common analysis procedure for the creep analysis of structures. The most recent programs are designed to handle a general class of material properties and are able to calculate elastic, plastic, and creep components of strain under general loading histories. The constant stress approach is too crude a model to accurately represent the actual behaviour of the stress for large time steps. The true path of a point in the effective stress-effective strain (sigmasup(e)-epsilonsup(c)) plane is often one in which the slope is rapidly changing. Thus the stress level quickly moves away from the initial stress level and then gradually approaches the final one. The result is that the assumed constant stress level quickly becomes inaccurate. What is required is a better method of approximation of the true path in the sigmasup(e)-epsilonsup(c) space. The method described here is called the path function approach because it employs an assumed function to estimate the motion of points in the sigmasup(e)-epsilonsup(c) space. (Auth.)

  18. Earthquake Hazard Analysis Methods: A Review

    Science.gov (United States)

    Sari, A. M.; Fakhrurrozi, A.

    2018-02-01

    One of natural disasters that have significantly impacted on risks and damage is an earthquake. World countries such as China, Japan, and Indonesia are countries located on the active movement of continental plates with more frequent earthquake occurrence compared to other countries. Several methods of earthquake hazard analysis have been done, for example by analyzing seismic zone and earthquake hazard micro-zonation, by using Neo-Deterministic Seismic Hazard Analysis (N-DSHA) method, and by using Remote Sensing. In its application, it is necessary to review the effectiveness of each technique in advance. Considering the efficiency of time and the accuracy of data, remote sensing is used as a reference to the assess earthquake hazard accurately and quickly as it only takes a limited time required in the right decision-making shortly after the disaster. Exposed areas and possibly vulnerable areas due to earthquake hazards can be easily analyzed using remote sensing. Technological developments in remote sensing such as GeoEye-1 provide added value and excellence in the use of remote sensing as one of the methods in the assessment of earthquake risk and damage. Furthermore, the use of this technique is expected to be considered in designing policies for disaster management in particular and can reduce the risk of natural disasters such as earthquakes in Indonesia.

  19. Sensitivity analysis of the Two Geometry Method

    International Nuclear Information System (INIS)

    Wichers, V.A.

    1993-09-01

    The Two Geometry Method (TGM) was designed specifically for the verification of the uranium enrichment of low enriched UF 6 gas in the presence of uranium deposits on the pipe walls. Complications can arise if the TGM is applied under extreme conditions, such as deposits larger than several times the gas activity, small pipe diameters less than 40 mm and low pressures less than 150 Pa. This report presents a comprehensive sensitivity analysis of the TGM. The impact of the various sources of uncertainty on the performance of the method is discussed. The application to a practical case is based on worst case conditions with regards to the measurement conditions, and on realistic conditions with respect to the false alarm probability and the non detection probability. Monte Carlo calculations were used to evaluate the sensitivity for sources of uncertainty which are experimentally inaccessible. (orig.)

  20. Blood proteins analysis by Raman spectroscopy method

    Science.gov (United States)

    Artemyev, D. N.; Bratchenko, I. A.; Khristoforova, Yu. A.; Lykina, A. A.; Myakinin, O. O.; Kuzmina, T. P.; Davydkin, I. L.; Zakharov, V. P.

    2016-04-01

    This work is devoted to study the possibility of plasma proteins (albumin, globulins) concentration measurement using Raman spectroscopy setup. The blood plasma and whole blood were studied in this research. The obtained Raman spectra showed significant variation of intensities of certain spectral bands 940, 1005, 1330, 1450 and 1650 cm-1 for different protein fractions. Partial least squares regression analysis was used for determination of correlation coefficients. We have shown that the proposed method represents the structure and biochemical composition of major blood proteins.

  1. Moessbauer lineshape analysis by the DISPA method

    International Nuclear Information System (INIS)

    Miglierini, M.; Sitek, J.

    1986-01-01

    To evaluate the Moessbauer spectral parameters and hence, the structural and magnetic properties the lineshape should be known. A plot of dispersion versus absorption (DISPA plot) for a pure Lorentzian gives a perfect circle. Directions and magnitudes of DISPA distortions from this reference circle point out the kind of line-broadening mechanism observed. A possibility of the application of the DISPA technique in the Moessbauer lineshape analysis is dealt with in this paper. The method is verified on Moessbauer spectra of sodium nitroprusside, natural iron, and stainless steel. The lineshape of an amorphous metallic alloy Fe 40 Ni 40 B 20 is studied by means of the DISPA plots. (author)

  2. Electromagnetic compatibility methods, analysis, circuits, and measurement

    CERN Document Server

    Weston, David A

    2016-01-01

    Revised, updated, and expanded, Electromagnetic Compatibility: Methods, Analysis, Circuits, and Measurement, Third Edition provides comprehensive practical coverage of the design, problem solving, and testing of electromagnetic compatibility (EMC) in electrical and electronic equipment and systems. This new edition provides novel information on theory, applications, evaluations, electromagnetic computational programs, and prediction techniques available. With sixty-nine schematics providing examples for circuit level electromagnetic interference (EMI) hardening and cost effective EMI problem solving, this book also includes 1130 illustrations and tables. Including extensive data on components and their correct implementation, the myths, misapplication, misconceptions, and fallacies that are common when discussing EMC/EMI will also be addressed and corrected.

  3. Method and apparatus for simultaneous spectroelectrochemical analysis

    Science.gov (United States)

    Chatterjee, Sayandev; Bryan, Samuel A; Schroll, Cynthia A; Heineman, William R

    2013-11-19

    An apparatus and method of simultaneous spectroelectrochemical analysis is disclosed. A transparent surface is provided. An analyte solution on the transparent surface is contacted with a working electrode and at least one other electrode. Light from a light source is focused on either a surface of the working electrode or the analyte solution. The light reflected from either the surface of the working electrode or the analyte solution is detected. The potential of the working electrode is adjusted, and spectroscopic changes of the analyte solution that occur with changes in thermodynamic potentials are monitored.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Coloured Petri Nets: Basic Concepts, Analysis Methods and Practical Use. Vol. 2, Analysis Methods

    DEFF Research Database (Denmark)

    Jensen, Kurt

    ideas behind the analysis methods are described as well as the mathematics on which they are based and also how the methods are supported by computer tools. Some parts of the volume are theoretical while others are application oriented. The purpose of the volume is to teach the reader how to use......This three-volume work presents a coherent description of the theoretical and practical aspects of coloured Petri nets (CP-nets). The second volume contains a detailed presentation of the analysis methods for CP-nets. They allow the modeller to investigate dynamic properties of CP-nets. The main...... the formal analysis methods, which does not require a deep understanding of the underlying mathematical theory....

  9. Economic analysis of alternative LLW disposal methods

    International Nuclear Information System (INIS)

    Foutes, C.E.; Queenan, C.J. III

    1987-01-01

    The Environmental Protection Agency (EPA) has evaluated the costs and benefits of alternative disposal technologies as part of its program to develop generally applicable environmental standards for the land disposal of low-level radioactive waste (LLW). Costs, population health effects and Critical Population Group (CPG) exposures resulting from alternative waste treatment and disposal methods were evaluated both in absolute terms and also relative to a base case (current practice). Incremental costs of the standard included costs for packaging, processing, transportation, and burial of waste. Benefits are defined in terms of reductions in the general population health risk (expected fatal cancers and genetic effects) evaluated over 10,000 years. A cost-effectiveness ratio, defined as the incremental cost per avoided health effect, was calculated for each alternative standard. The cost-effectiveness analysis took into account a number of waste streams, hydrogeologic and climatic region settings, and waste treatment and disposal methods. This paper describes the alternatives considered and preliminary results of the cost-effectiveness analysis. 15 references, 7 figures, 3 tables

  10. Analysis of methods. [information systems evolution environment

    Science.gov (United States)

    Mayer, Richard J. (Editor); Ackley, Keith A.; Wells, M. Sue; Mayer, Paula S. D.; Blinn, Thomas M.; Decker, Louis P.; Toland, Joel A.; Crump, J. Wesley; Menzel, Christopher P.; Bodenmiller, Charles A.

    1991-01-01

    Information is one of an organization's most important assets. For this reason the development and maintenance of an integrated information system environment is one of the most important functions within a large organization. The Integrated Information Systems Evolution Environment (IISEE) project has as one of its primary goals a computerized solution to the difficulties involved in the development of integrated information systems. To develop such an environment a thorough understanding of the enterprise's information needs and requirements is of paramount importance. This document is the current release of the research performed by the Integrated Development Support Environment (IDSE) Research Team in support of the IISEE project. Research indicates that an integral part of any information system environment would be multiple modeling methods to support the management of the organization's information. Automated tool support for these methods is necessary to facilitate their use in an integrated environment. An integrated environment makes it necessary to maintain an integrated database which contains the different kinds of models developed under the various methodologies. In addition, to speed the process of development of models, a procedure or technique is needed to allow automatic translation from one methodology's representation to another while maintaining the integrity of both. The purpose for the analysis of the modeling methods included in this document is to examine these methods with the goal being to include them in an integrated development support environment. To accomplish this and to develop a method for allowing intra-methodology and inter-methodology model element reuse, a thorough understanding of multiple modeling methodologies is necessary. Currently the IDSE Research Team is investigating the family of Integrated Computer Aided Manufacturing (ICAM) DEFinition (IDEF) languages IDEF(0), IDEF(1), and IDEF(1x), as well as ENALIM, Entity

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. Chapter 11. Community analysis-based methods

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Y.; Wu, C.H.; Andersen, G.L.; Holden, P.A.

    2010-05-01

    Microbial communities are each a composite of populations whose presence and relative abundance in water or other environmental samples are a direct manifestation of environmental conditions, including the introduction of microbe-rich fecal material and factors promoting persistence of the microbes therein. As shown by culture-independent methods, different animal-host fecal microbial communities appear distinctive, suggesting that their community profiles can be used to differentiate fecal samples and to potentially reveal the presence of host fecal material in environmental waters. Cross-comparisons of microbial communities from different hosts also reveal relative abundances of genetic groups that can be used to distinguish sources. In increasing order of their information richness, several community analysis methods hold promise for MST applications: phospholipid fatty acid (PLFA) analysis, denaturing gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism (TRFLP), cloning/sequencing, and PhyloChip. Specific case studies involving TRFLP and PhyloChip approaches demonstrate the ability of community-based analyses of contaminated waters to confirm a diagnosis of water quality based on host-specific marker(s). The success of community-based MST for comprehensively confirming fecal sources relies extensively upon using appropriate multivariate statistical approaches. While community-based MST is still under evaluation and development as a primary diagnostic tool, results presented herein demonstrate its promise. Coupled with its inherently comprehensive ability to capture an unprecedented amount of microbiological data that is relevant to water quality, the tools for microbial community analysis are increasingly accessible, and community-based approaches have unparalleled potential for translation into rapid, perhaps real-time, monitoring platforms.

  16. Cleanup standards and pathways analysis methods

    International Nuclear Information System (INIS)

    Devgun, J.S.

    1993-01-01

    Remediation of a radioactively contaminated site requires that certain regulatory criteria be met before the site can be released for unrestricted future use. Since the ultimate objective of remediation is to protect the public health and safety, residual radioactivity levels remaining at a site after cleanup must be below certain preset limits or meet acceptable dose or risk criteria. Release of a decontaminated site requires proof that the radiological data obtained from the site meet the regulatory criteria for such a release. Typically release criteria consist of a composite of acceptance limits that depend on the radionuclides, the media in which they are present, and federal and local regulations. In recent years, the US Department of Energy (DOE) has developed a pathways analysis model to determine site-specific soil activity concentration guidelines for radionuclides that do not have established generic acceptance limits. The DOE pathways analysis computer code (developed by Argonne National Laboratory for the DOE) is called RESRAD (Gilbert et al. 1989). Similar efforts have been initiated by the US Nuclear Regulatory Commission (NRC) to develop and use dose-related criteria based on genetic pathways analyses rather than simplistic numerical limits on residual radioactivity. The focus of this paper is radionuclide contaminated soil. Cleanup standards are reviewed, pathways analysis methods are described, and an example is presented in which RESRAD was used to derive cleanup guidelines

  17. 3D analysis methods - Study and seminar

    International Nuclear Information System (INIS)

    Daaviittila, A.

    2003-10-01

    The first part of the report results from a study that was performed as a Nordic co-operation activity with active participation from Studsvik Scandpower and Westinghouse Atom in Sweden, and VTT in Finland. The purpose of the study was to identify and investigate the effects rising from using the 3D transient com-puter codes in BWR safety analysis, and their influence on the transient analysis methodology. One of the main questions involves the critical power ratio (CPR) calculation methodology. The present way, where the CPR calculation is per-formed with a separate hot channel calculation, can be artificially conservative. In the investigated cases, no dramatic minimum CPR effect coming from the 3D calculation is apparent. Some cases show some decrease in the transient change of minimum CPR with the 3D calculation, which confirms the general thinking that the 1D calculation is conservative. On the other hand, the observed effect on neutron flux behaviour is quite large. In a slower transient the 3D effect might be stronger. The second part of the report is a summary of a related seminar that was held on the 3D analysis methods. The seminar was sponsored by the Reactor Safety part (NKS-R) of the Nordic Nuclear Safety Research Programme (NKS). (au)

  18. Generalized Analysis of a Distribution Separation Method

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2016-04-01

    Full Text Available Separating two probability distributions from a mixture model that is made up of the combinations of the two is essential to a wide range of applications. For example, in information retrieval (IR, there often exists a mixture distribution consisting of a relevance distribution that we need to estimate and an irrelevance distribution that we hope to get rid of. Recently, a distribution separation method (DSM was proposed to approximate the relevance distribution, by separating a seed irrelevance distribution from the mixture distribution. It was successfully applied to an IR task, namely pseudo-relevance feedback (PRF, where the query expansion model is often a mixture term distribution. Although initially developed in the context of IR, DSM is indeed a general mathematical formulation for probability distribution separation. Thus, it is important to further generalize its basic analysis and to explore its connections to other related methods. In this article, we first extend DSM’s theoretical analysis, which was originally based on the Pearson correlation coefficient, to entropy-related measures, including the KL-divergence (Kullback–Leibler divergence, the symmetrized KL-divergence and the JS-divergence (Jensen–Shannon divergence. Second, we investigate the distribution separation idea in a well-known method, namely the mixture model feedback (MMF approach. We prove that MMF also complies with the linear combination assumption, and then, DSM’s linear separation algorithm can largely simplify the EM algorithm in MMF. These theoretical analyses, as well as further empirical evaluation results demonstrate the advantages of our DSM approach.

  19. Method development for trace and ultratrace analysis

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    Method development, that is, selection of a mode of chromatography and the right column and mobile-phase combination for trace and ultratrace analysis, requires several main considerations. The method should be useful for resolving various trace and ultratrace components present in the sample. If the nature of these components is known, the choice of method may be straightforward, that is, a selection can be made from the following modes of HPLC: (1) adsorption chromatography; (2) normal-phase chromatography; (3) reversed-phase chromatography; (4) ion-pair chromatography; (5) ion-exchange chromatography; (6) ion chromatography. Unfortunately, the nature of all of the components is frequently unknown. However, several intelligent judgments can be made on the nature of impurities. This chapter deals with some basic approaches to mobile-phase selection and optimization. More detailed information may be found in basic texts. Techniques for separation of high-molecular-weight compounds (macromolecules) and chiral compounds may be found elsewhere. Mainly compounds with molecular weight lower than 2,000 are discussed here. 123 refs

  20. Novel Method of Production Decline Analysis

    Science.gov (United States)

    Xie, Shan; Lan, Yifei; He, Lei; Jiao, Yang; Wu, Yong

    2018-02-01

    ARPS decline curves is the most commonly used in oil and gas field due to its minimal data requirements and ease application. And prediction of production decline which is based on ARPS analysis rely on known decline type. However, when coefficient index are very approximate under different decline type, it is difficult to directly recognize decline trend of matched curves. Due to difficulties above, based on simulation results of multi-factor response experiments, a new dynamic decline prediction model is introduced with using multiple linear regression of influence factors. First of all, according to study of effect factors of production decline, interaction experimental schemes are designed. Based on simulated results, annual decline rate is predicted by decline model. Moreover, the new method is applied in A gas filed of Ordos Basin as example to illustrate reliability. The result commit that the new model can directly predict decline tendency without needing recognize decline style. From arithmetic aspect, it also take advantage of high veracity. Finally, the new method improves the evaluation method of gas well production decline in low permeability gas reservoir, which also provides technical support for further understanding of tight gas field development laws.

  1. Phylogenetic analysis using parsimony and likelihood methods.

    Science.gov (United States)

    Yang, Z

    1996-02-01

    The assumptions underlying the maximum-parsimony (MP) method of phylogenetic tree reconstruction were intuitively examined by studying the way the method works. Computer simulations were performed to corroborate the intuitive examination. Parsimony appears to involve very stringent assumptions concerning the process of sequence evolution, such as constancy of substitution rates between nucleotides, constancy of rates across nucleotide sites, and equal branch lengths in the tree. For practical data analysis, the requirement of equal branch lengths means similar substitution rates among lineages (the existence of an approximate molecular clock), relatively long interior branches, and also few species in the data. However, a small amount of evolution is neither a necessary nor a sufficient requirement of the method. The difficulties involved in the application of current statistical estimation theory to tree reconstruction were discussed, and it was suggested that the approach proposed by Felsenstein (1981, J. Mol. Evol. 17: 368-376) for topology estimation, as well as its many variations and extensions, differs fundamentally from the maximum likelihood estimation of a conventional statistical parameter. Evidence was presented showing that the Felsenstein approach does not share the asymptotic efficiency of the maximum likelihood estimator of a statistical parameter. Computer simulations were performed to study the probability that MP recovers the true tree under a hierarchy of models of nucleotide substitution; its performance relative to the likelihood method was especially noted. The results appeared to support the intuitive examination of the assumptions underlying MP. When a simple model of nucleotide substitution was assumed to generate data, the probability that MP recovers the true topology could be as high as, or even higher than, that for the likelihood method. When the assumed model became more complex and realistic, e.g., when substitution rates were

  2. External event analysis methods for NUREG-1150

    International Nuclear Information System (INIS)

    Bohn, M.P.; Lambright, J.A.

    1989-01-01

    The US Nuclear Regulatory Commission is sponsoring probabilistic risk assessments of six operating commercial nuclear power plants as part of a major update of the understanding of risk as provided by the original WASH-1400 risk assessments. In contrast to the WASH-1400 studies, at least two of the NUREG-1150 risk assessments will include an analysis of risks due to earthquakes, fires, floods, etc., which are collectively known as eternal events. This paper summarizes the methods to be used in the external event analysis for NUREG-1150 and the results obtained to date. The two plants for which external events are being considered are Surry and Peach Bottom, a PWR and BWR respectively. The external event analyses (through core damage frequency calculations) were completed in June 1989, with final documentation available in September. In contrast to most past external event analyses, wherein rudimentary systems models were developed reflecting each external event under consideration, the simplified NUREG-1150 analyses are based on the availability of the full internal event PRA systems models (event trees and fault trees) and make use of extensive computer-aided screening to reduce them to sequence cut sets important to each external event. This provides two major advantages in that consistency and scrutability with respect to the internal event analysis is achieved, and the full gamut of random and test/maintenance unavailabilities are automatically included, while only those probabilistically important survive the screening process. Thus, full benefit of the internal event analysis is obtained by performing the internal and external event analyses sequentially

  3. 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

  4. 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.

  5. Spectral Analysis Methods of Social Networks

    Directory of Open Access Journals (Sweden)

    P. G. Klyucharev

    2017-01-01

    Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work

  6. Method and tool for network vulnerability analysis

    Science.gov (United States)

    Swiler, Laura Painton [Albuquerque, NM; Phillips, Cynthia A [Albuquerque, NM

    2006-03-14

    A computer system analysis tool and method that will allow for qualitative and quantitative assessment of security attributes and vulnerabilities in systems including computer networks. The invention is based on generation of attack graphs wherein each node represents a possible attack state and each edge represents a change in state caused by a single action taken by an attacker or unwitting assistant. Edges are weighted using metrics such as attacker effort, likelihood of attack success, or time to succeed. Generation of an attack graph is accomplished by matching information about attack requirements (specified in "attack templates") to information about computer system configuration (contained in a configuration file that can be updated to reflect system changes occurring during the course of an attack) and assumed attacker capabilities (reflected in "attacker profiles"). High risk attack paths, which correspond to those considered suited to application of attack countermeasures given limited resources for applying countermeasures, are identified by finding "epsilon optimal paths."

  7. 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.

  8. Quantitative Risk Analysis: Method And Process

    Directory of Open Access Journals (Sweden)

    Anass BAYAGA

    2010-03-01

    Full Text Available Recent and past studies (King III report, 2009: 73-75; Stoney 2007;Committee of Sponsoring Organisation-COSO, 2004, Bartell, 2003; Liebenberg and Hoyt, 2003; Reason, 2000; Markowitz 1957 lament that although, the introduction of quantifying risk to enhance degree of objectivity in finance for instance was quite parallel to its development in the manufacturing industry, it is not the same in Higher Education Institution (HEI. In this regard, the objective of the paper was to demonstrate the methods and process of Quantitative Risk Analysis (QRA through likelihood of occurrence of risk (phase I. This paper serves as first of a two-phased study, which sampled hundred (100 risk analysts in a University in the greater Eastern Cape Province of South Africa.The analysis of likelihood of occurrence of risk by logistic regression and percentages were conducted to investigate whether there were a significant difference or not between groups (analyst in respect of QRA.The Hosmer and Lemeshow test was non-significant with a chi-square(X2 =8.181; p = 0.300, which indicated that there was a good model fit, since the data did not significantly deviate from the model. The study concluded that to derive an overall likelihood rating that indicated the probability that a potential risk may be exercised within the construct of an associated threat environment, the following governing factors must be considered: (1 threat source motivation and capability (2 nature of the vulnerability (3 existence and effectiveness of current controls (methods and process.

  9. Preliminary hazard analysis using sequence tree method

    International Nuclear Information System (INIS)

    Huang Huiwen; Shih Chunkuan; Hung Hungchih; Chen Minghuei; Yih Swu; Lin Jiinming

    2007-01-01

    A system level PHA using sequence tree method was developed to perform Safety Related digital I and C system SSA. The conventional PHA is a brainstorming session among experts on various portions of the system to identify hazards through discussions. However, this conventional PHA is not a systematic technique, the analysis results strongly depend on the experts' subjective opinions. The analysis quality cannot be appropriately controlled. Thereby, this research developed a system level sequence tree based PHA, which can clarify the relationship among the major digital I and C systems. Two major phases are included in this sequence tree based technique. The first phase uses a table to analyze each event in SAR Chapter 15 for a specific safety related I and C system, such as RPS. The second phase uses sequence tree to recognize what I and C systems are involved in the event, how the safety related systems work, and how the backup systems can be activated to mitigate the consequence if the primary safety systems fail. In the sequence tree, the defense-in-depth echelons, including Control echelon, Reactor trip echelon, ESFAS echelon, and Indication and display echelon, are arranged to construct the sequence tree structure. All the related I and C systems, include digital system and the analog back-up systems are allocated in their specific echelon. By this system centric sequence tree based analysis, not only preliminary hazard can be identified systematically, the vulnerability of the nuclear power plant can also be recognized. Therefore, an effective simplified D3 evaluation can be performed as well. (author)

  10. CARBON SEQUESTRATION: A METHODS COMPARATIVE ANALYSIS

    International Nuclear Information System (INIS)

    Christopher J. Koroneos; Dimitrios C. Rovas

    2008-01-01

    All human activities are related with the energy consumption. Energy requirements will continue to rise, due to the modern life and the developing countries growth. Most of the energy demand emanates from fossil fuels. Fossil fuels combustion has negative environmental impacts, with the CO 2 production to be dominating. The fulfillment of the Kyoto protocol criteria requires the minimization of CO 2 emissions. Thus the management of the CO 2 emissions is an urgent matter. The use of appliances with low energy use and the adoption of an energy policy that prevents the unnecessary energy use, can play lead to the reduction of carbon emissions. A different route is the introduction of ''clean'' energy sources, such as renewable energy sources. Last but not least, the development of carbon sequestration methods can be promising technique with big future potential. The objective of this work is the analysis and comparison of different carbon sequestration and deposit methods. Ocean deposit, land ecosystems deposit, geological formations deposit and radical biological and chemical approaches will be analyzed

  11. Recent improvement of the resonance analysis methods

    International Nuclear Information System (INIS)

    Sirakov, I.; Lukyanov, A.

    2000-01-01

    By the use of a two-step method called Combined, the R-matrix Wigner-Eisenbud representation in the resonance reaction theory has been converted into other equivalent representations (parameterizations) of the collision matrix with Poles in E domain. Two of them called Capture Elimination (CE) and Reaction Elimination (RE) representation respectively, have energy independent parameters and are both rigorous and applicable. The CE representation is essentially a generalization of the Reich-Moore (RM) formalism. The RE representation, in turn, offers some distinct advantages when analyzing fissile nuclei. The latter does not require any approximation for the capture channels and does not need any assumption about the number of fission channels in contrast to the RM representation. Unlike the RM parameters the RE ones are uniquely determined for applications in the resonance analysis. When given in the RE representation, neutron cross sections of fissile nuclei in the resolved resonance region are presented through simple scalar expressions without the need of matrix inversion. Various computer codes have been developed to demonstrate the viability of the new method. The RM parameters of the fissile nuclei have been converted into equivalent RE parameters implying the RM assumptions (REFINE code). Conversely, the RE parameters have been converted into corresponding RM parameters when one fission channel is present and the RM parameter set is unique, e.g. Pu-239, J =1 (REVERSE code). To further enhance the flexibility of the proposed method the obtained RE parameters have been converted into equivalent Generalized Pole parameters (REFILE code), which are parameters of the rigorous pole expansion of the collision matrix in √E domain. equi valent sets of RM, RE and GP parameters of 239 Pu are given as an example. It has been pointed out that all the advantages of the newly proposed representation can be implemented through an independent evaluation of the RE resonance

  12. Analysis of thermal power calibration method

    International Nuclear Information System (INIS)

    Zagar, T.; Ravnik, M.; Persic, A.

    2000-01-01

    The methods for determining fuel element burnup have recently become interesting because of activities related to the shipment of highly enriched fuel elements back to the United States for final disposal before 2009. The most common and practical method for determining fuel element burnup in research reactors is reactor calculation. Experience has shown that burnup calculations become complicated and biased with uncertainties if a long period of reactor operation must be reproduced. Besides this, accuracy of calculated burnup is always limited with accuracy of reactor power calibration, since burnup calculation is based on calculated power density distribution, which is usually expressed in terms of power released per fuel element and normalised to the reactor power It is obvious that reactor thermal power calibration is very important for precise fuel element burnup calculation. Calculated fuel element burnup is linearly dependent on the thermal reactor power. The reactor power level may be determined from measured absolute thermal flux distribution across the core in the horizontal and vertical planes. Flux distributions are measured with activation of cadmium covered and bare foils irradiated by the steady reactor power. But it should be realised that this method is time consuming and not accurate. This method is practical only for zero power reactors and is in practice very seldom performed for other reactors (e.g. for TRIGA reactor in Ljubljana absolute thermal flux distribution was not performed since reactor reconstruction in 1991). In case of power reactors and research reactors in which a temperature rise across the core is produced and measured than a heat balance method is the most common and accurate method of determining the power output of the core. The purpose of this paper is to analyse the accuracy of calorimetric reactor power calibration method and to analyse the influence of control rod position on nuclear detector reading for TRIGA reactors

  13. 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)

  14. 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)

  15. DORIAN, Bayes Method Plant Age Risk Analysis

    International Nuclear Information System (INIS)

    Atwood, C.L.

    2002-01-01

    1 - Description of program or function: DORIAN is an integrated package for performing Bayesian aging analysis of reliability data; e.g. for identifying trends in component failure rates and/or outage durations as a function of time. The user must specify several alternative hypothesized 'aging models' (i.e., possible trends) along prior probabilities indicating the subject probability that each trend is actually the correct one. DORIAN then uses component failure and/or repair data over time to update these prior probabilities and develop a posterior probability for each aging model, representing the probability that each model is the correct one in light of the observed data rather than a priori. Mean, median, and 5. and 95. percentile trends are also compiled from the posterior probabilities. 2 - Method of solution: DORIAN carries out a Bayesian analysis of failure data and a prior distribution on a time-dependent failure rate to obtain a posterior distribution on the failure rate. The form of the time-dependent failure rate is arbitrary, because DORIAN approximates the form by a step-function, constant within specified time intervals. Similarly, the parameters may have any prior distribution, because DORIAN uses a discrete distribution to approximate this. Likewise, the database file produced by DORIAN approximates the entire range of possible failure rates or outage durations developed by means of a discrete probability distribution containing no more than 20 distinct values with their probabilities. 3 - Restrictions on the complexity of the problem: Prior distribution is discrete with up to 25 values. Up to 60 times are accommodated in the discrete time history

  16. Synthesis and in Vitro Antioxidant Activity Evaluation of 3-Carboxycoumarin Derivatives and QSAR Study of Their DPPH• Radical Scavenging Activity

    Directory of Open Access Journals (Sweden)

    Maria Teresa Sumaya-Martínez

    2012-12-01

    Full Text Available The in vitro antioxidant activities of eight 3-carboxycoumarin derivatives were assayed by the quantitative 1,1-diphenyl-2-picrylhydrazil (DPPH• radical scavenging activity method. 3-Acetyl-6-hydroxy-2H-1-benzopyran-2-one (C1 and ethyl 6-hydroxy-2-oxo-2H-1-benzopyran-3-carboxylate (C2 presented the best radical-scavenging activity. A quantitative structure-activity relationship (QSAR study was performed and correlated with the experimental DPPH• scavenging data. We used structural, geometrical, topological and quantum-chemical descriptors selected with Genetic Algorithms in order to determine which of these parameters are responsible of the observed DPPH• radical scavenging activity. We constructed a back propagation neural network with the hydrophilic factor (Hy descriptor to generate an adequate architecture of neurons for the system description. The mathematical model showed a multiple determination coefficient of 0.9196 and a root mean squared error of 0.0851. Our results shows that the presence of hydroxyl groups on the ring structure of 3-carboxy-coumarins are correlated with the observed DPPH• radical scavenging activity effects.

  17. 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.

  18. An Analysis of the SURF Method

    Directory of Open Access Journals (Sweden)

    Edouard Oyallon

    2015-07-01

    Full Text Available The SURF method (Speeded Up Robust Features is a fast and robust algorithm for local, similarity invariant representation and comparison of images. Similarly to many other local descriptor-based approaches, interest points of a given image are defined as salient features from a scale-invariant representation. Such a multiple-scale analysis is provided by the convolution of the initial image with discrete kernels at several scales (box filters. The second step consists in building orientation invariant descriptors, by using local gradient statistics (intensity and orientation. The main interest of the SURF approach lies in its fast computation of operators using box filters, thus enabling real-time applications such as tracking and object recognition. The SURF framework described in this paper is based on the PhD thesis of H. Bay [ETH Zurich, 2009], and more specifically on the paper co-written by H. Bay, A. Ess, T. Tuytelaars and L. Van Gool [Computer Vision and Image Understanding, 110 (2008, pp. 346–359]. An implementation is proposed and used to illustrate the approach for image matching. A short comparison with a state-of-the-art approach is also presented, the SIFT algorithm of D. Lowe [International Journal of Computer Vision, 60 (2004, pp. 91–110], with which SURF shares a lot in common.

  19. Analysis methods used by the geochemistry department

    International Nuclear Information System (INIS)

    Berthollet, P.

    1958-06-01

    This note presents various analytical techniques which are respectively used for the dosing of uranium in soils (fluorescence method, chromatographic method), for the dosing of uranium in natural waters (ion exchange method, evaporation method), and for the dosing of uranium in plants. Principles, equipment and products, reactant preparation, operation mode, sample preparation and measurements, expression of results and calculations) are indicated for each of these methods

  20. 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

  1. Instrumental neutron activation analysis - a routine method

    International Nuclear Information System (INIS)

    Bruin, M. de.

    1983-01-01

    This thesis describes the way in which at IRI instrumental neutron activation analysis (INAA) has been developed into an automated system for routine analysis. The basis of this work are 20 publications describing the development of INAA since 1968. (Auth.)

  2. Basic methods of linear functional analysis

    CERN Document Server

    Pryce, John D

    2011-01-01

    Introduction to the themes of mathematical analysis, geared toward advanced undergraduate and graduate students. Topics include operators, function spaces, Hilbert spaces, and elementary Fourier analysis. Numerous exercises and worked examples.1973 edition.

  3. 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.

  4. Applying homotopy analysis method for solving differential-difference equation

    International Nuclear Information System (INIS)

    Wang Zhen; Zou Li; Zhang Hongqing

    2007-01-01

    In this Letter, we apply the homotopy analysis method to solving the differential-difference equations. A simple but typical example is applied to illustrate the validity and the great potential of the generalized homotopy analysis method in solving differential-difference equation. Comparisons are made between the results of the proposed method and exact solutions. The results show that the homotopy analysis method is an attractive method in solving the differential-difference equations

  5. 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.

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

    Science.gov (United States)

    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.

  7. 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.

  8. 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.

  9. 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.

  10. 2. Methods of elemental analysis of materials

    International Nuclear Information System (INIS)

    Musilek, L.

    1992-01-01

    The principles of activation analysis are outlined including the preparation of samples and reference materials, the choice of suitable activation sources, interfering effects, detection of radiation emitted and analysis of mixtures of emitters, and the potential of activation analysis in various fields of science and technology. The principles of X-ray fluorescence analysis and the associated instrumentation are also dealt with, and examples of applications are given. Described are also the physical nature of the Moessbauer effect, Moessbauer sources and spectrometers, and the applicability of this effect in physical research and in the investigation of iron-containing materials. (Z.S.). 1 tab., 20 figs., 90 refs

  11. Extension and Validation of UNDEX Analysis Methods

    National Research Council Canada - National Science Library

    Donahue, L

    2004-01-01

    .... Adaptive grid schemes for underwater shock and bubble analysis, hydrostatic pressure and airwater/seafloor boundaries, underwater explosion profiles, and fluid-backed shapes were also implemented...

  12. Response matrix method for large LMFBR analysis

    International Nuclear Information System (INIS)

    King, M.J.

    1977-06-01

    The feasibility of using response matrix techniques for computational models of large LMFBRs is examined. Since finite-difference methods based on diffusion theory have generally found a place in fast-reactor codes, a brief review of their general matrix foundation is given first in order to contrast it to the general strategy of response matrix methods. Then, in order to present the general method of response matrix technique, two illustrative examples are given. Matrix algorithms arising in the application to large LMFBRs are discussed, and the potential of the response matrix method is explored for a variety of computational problems. Principal properties of the matrices involved are derived with a view to application of numerical methods of solution. The Jacobi iterative method as applied to the current-balance eigenvalue problem is discussed

  13. Climate Action Benefits: Methods of Analysis

    Science.gov (United States)

    This page provides detailed information on the methods used in the CIRA analyses, including the overall framework, temperature projections, precipitation projections, sea level rise projections, uncertainty, and limitations.

  14. Numerical analysis in electromagnetics the TLM method

    CERN Document Server

    Saguet, Pierre

    2013-01-01

    The aim of this book is to give a broad overview of the TLM (Transmission Line Matrix) method, which is one of the "time-domain numerical methods". These methods are reputed for their significant reliance on computer resources. However, they have the advantage of being highly general.The TLM method has acquired a reputation for being a powerful and effective tool by numerous teams and still benefits today from significant theoretical developments. In particular, in recent years, its ability to simulate various situations with excellent precision, including complex materials, has been

  15. Methods for Mediation Analysis with Missing Data

    Science.gov (United States)

    Zhang, Zhiyong; Wang, Lijuan

    2013-01-01

    Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…

  16. Development of analysis methods for seismically isolated nuclear structures

    International Nuclear Information System (INIS)

    Yoo, Bong; Lee, Jae-Han; Koo, Gyeng-Hoi

    2002-01-01

    KAERI's contributions to the project entitled Development of Analysis Methods for Seismically Isolated Nuclear Structures under IAEA CRP of the intercomparison of analysis methods for predicting the behaviour of seismically isolated nuclear structures during 1996-1999 in effort to develop the numerical analysis methods and to compare the analysis results with the benchmark test results of seismic isolation bearings and isolated nuclear structures provided by participating countries are briefly described. Certain progress in the analysis procedures for isolation bearings and isolated nuclear structures has been made throughout the IAEA CRPs and the analysis methods developed can be improved for future nuclear facility applications. (author)

  17. 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.

  18. Predicting the cross-reactivities of polycyclic aromatic hydrocarbons in ELISA by regression analysis and CoMFA methods

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yan-Feng; Dai, Shu-Gui [College of Environmental Science and Engineering, Nankai University, Key Laboratory for Pollution Process and Environmental Criteria of Ministry of Education, Tianjin (China); Ma, Yi [College of Chemistry, Nankai University, Institute of Elemento-Organic Chemistry, Tianjin (China); Gao, Zhi-Xian [Institute of Hygiene and Environmental Medicine, Tianjin (China)

    2010-07-15

    Immunoassays have been regarded as a possible alternative or supplement for measuring polycyclic aromatic hydrocarbons (PAHs) in the environment. Since there are too many potential cross-reactants for PAH immunoassays, it is difficult to determine all the cross-reactivities (CRs) by experimental tests. The relationship between CR and the physical-chemical properties of PAHs and related compounds was investigated using the CR data from a commercial enzyme-linked immunosorbent assay (ELISA) kit test. Two quantitative structure-activity relationship (QSAR) techniques, regression analysis and comparative molecular field analysis (CoMFA), were applied for predicting the CR of PAHs in this ELISA kit. Parabolic regression indicates that the CRs are significantly correlated with the logarithm of the partition coefficient for the octanol-water system (log K{sub ow}) (r{sup 2}=0.643, n=23, P<0.0001), suggesting that hydrophobic interactions play an important role in the antigen-antibody binding and the cross-reactions in this ELISA test. The CoMFA model obtained shows that the CRs of the PAHs are correlated with the 3D structure of the molecules (r{sub cv}{sup 2}=0.663, r{sup 2}=0.873, F{sub 4,32}=55.086). The contributions of the steric and electrostatic fields to CR were 40.4 and 59.6%, respectively. Both of the QSAR models satisfactorily predict the CR in this PAH immunoassay kit, and help in understanding the mechanisms of antigen-antibody interaction. (orig.)

  19. Evaluation of Novel Dual Acetyl- and Butyrylcholinesterase Inhibitors as Potential Anti-Alzheimer’s Disease Agents Using Pharmacophore, 3D-QSAR, and Molecular Docking Approaches

    Directory of Open Access Journals (Sweden)

    Xiaocong Pang

    2017-07-01

    Full Text Available DL0410, containing biphenyl and piperidine skeletons, was identified as an acetylcholinesterase (AChE and butyrylcholinesterase (BuChE inhibitor through high-throughput screening assays, and further studies affirmed its efficacy and safety for Alzheimer’s disease treatment. In our study, a series of novel DL0410 derivatives were evaluated for inhibitory activities towards AChE and BuChE. Among these derivatives, compounds 6-1 and 7-6 showed stronger AChE and BuChE inhibitory activities than DL0410. Then, pharmacophore modeling and three-dimensional quantitative structure activity relationship (3D-QSAR models were performed. The R2 of AChE and BuChE 3D-QSAR models for training set were found to be 0.925 and 0.883, while that of the test set were 0.850 and 0.881, respectively. Next, molecular docking methods were utilized to explore the putative binding modes. Compounds 6-1 and 7-6 could interact with the amino acid residues in the catalytic anionic site (CAS and peripheral anionic site (PAS of AChE/BuChE, which was similar with DL0410. Kinetics studies also suggested that the three compounds were all mixed-types of inhibitors. In addition, compound 6-1 showed better absorption and blood brain barrier permeability. These studies provide better insight into the inhibitory behaviors of DL0410 derivatives, which is beneficial for rational design of AChE and BuChE inhibitors in the future.

  20. Methods of stability analysis in nonlinear mechanics

    International Nuclear Information System (INIS)

    Warnock, R.L.; Ruth, R.D.; Gabella, W.; Ecklund, K.

    1989-01-01

    We review our recent work on methods to study stability in nonlinear mechanics, especially for the problems of particle accelerators, and compare our ideals to those of other authors. We emphasize methods that (1) show promise as practical design tools, (2) are effective when the nonlinearity is large, and (3) have a strong theoretical basis. 24 refs., 2 figs., 2 tabs

  1. Nuclear analysis methods in monitoring occupational health

    International Nuclear Information System (INIS)

    Clayton, E.

    1985-01-01

    With the increasing industrialisation of the world has come an increase in exposure to hazardous chemicals. Their effect on the body depends upon the concentration of the element in the work environment; its chemical form; the possible different routes of intake; and the individual's biological response to the chemical. Nuclear techniques of analysis such as neutron activation analysis (NAA) and proton induced X-ray emission analysis (PIXE), have played an important role in understanding the effects hazardous chemicals can have on occupationally exposed workers. In this review, examples of their application, mainly in monitoring exposure to heavy metals is discussed

  2. 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.

  3. Investigation of Antileishmanial Activities of Acridines Derivatives against Promastigotes and Amastigotes Form of Parasites Using Quantitative Structure Activity Relationship Analysis

    Directory of Open Access Journals (Sweden)

    Samir Chtita

    2016-01-01

    Full Text Available In a search of newer and potent antileishmanial (against promastigotes and amastigotes form of parasites drug, a series of 60 variously substituted acridines derivatives were subjected to a quantitative structure activity relationship (QSAR analysis for studying, interpreting, and predicting activities and designing new compounds by using multiple linear regression and artificial neural network (ANN methods. The used descriptors were computed with Gaussian 03, ACD/ChemSketch, Marvin Sketch, and ChemOffice programs. The QSAR models developed were validated according to the principles set up by the Organisation for Economic Co-operation and Development (OECD. The principal component analysis (PCA has been used to select descriptors that show a high correlation with activities. The univariate partitioning (UP method was used to divide the dataset into training and test sets. The multiple linear regression (MLR method showed a correlation coefficient of 0.850 and 0.814 for antileishmanial activities against promastigotes and amastigotes forms of parasites, respectively. Internal and external validations were used to determine the statistical quality of QSAR of the two MLR models. The artificial neural network (ANN method, considering the relevant descriptors obtained from the MLR, showed a correlation coefficient of 0.933 and 0.918 with 7-3-1 and 6-3-1 ANN models architecture for antileishmanial activities against promastigotes and amastigotes forms of parasites, respectively. The applicability domain of MLR models was investigated using simple and leverage approaches to detect outliers and outsides compounds. The effects of different descriptors in the activities were described and used to study and design new compounds with higher activities compared to the existing ones.

  4. Computational methods for corpus annotation and analysis

    CERN Document Server

    Lu, Xiaofei

    2014-01-01

    This book reviews computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, with instructions on how to obtain, install and use each tool. Covers studies using Natural Language Processing, and offers ideas for better integration.

  5. Progress in spatial analysis methods and applications

    CERN Document Server

    Páez, Antonio; Buliung, Ron N; Dall'erba, Sandy

    2010-01-01

    This book brings together developments in spatial analysis techniques, including spatial statistics, econometrics, and spatial visualization, and applications to fields such as regional studies, transportation and land use, population and health.

  6. Analysis of queues methods and applications

    CERN Document Server

    Gautam, Natarajan

    2012-01-01

    Introduction Analysis of Queues: Where, What, and How?Systems Analysis: Key ResultsQueueing Fundamentals and Notations Psychology in Queueing Reference Notes Exercises Exponential Interarrival and Service Times: Closed-Form Expressions Solving Balance Equations via Arc CutsSolving Balance Equations Using Generating Functions Solving Balance Equations Using Reversibility Reference Notes ExercisesExponential Interarrival and Service Times: Numerical Techniques and Approximations Multidimensional Birth and Death ChainsMultidimensional Markov Chains Finite-State Markov ChainsReference Notes Exerci

  7. Analysis of Non Local Image Denoising Methods

    Science.gov (United States)

    Pardo, Álvaro

    Image denoising is probably one of the most studied problems in the image processing community. Recently a new paradigm on non local denoising was introduced. The Non Local Means method proposed by Buades, Morel and Coll attracted the attention of other researches who proposed improvements and modifications to their proposal. In this work we analyze those methods trying to understand their properties while connecting them to segmentation based on spectral graph properties. We also propose some improvements to automatically estimate the parameters used on these methods.

  8. Analysis of the sweeped actuator line method

    OpenAIRE

    Nathan Jörn; Masson Christian; Dufresne Louis; Churchfield Matthew

    2015-01-01

    The actuator line method made it possible to describe the near wake of a wind turbine more accurately than with the actuator disk method. Whereas the actuator line generates the helicoidal vortex system shed from the tip blades, the actuator disk method sheds a vortex sheet from the edge of the rotor plane. But with the actuator line come also temporal and spatial constraints, such as the need for a much smaller time step than with actuator disk. While the latter one only has to obey the Cour...

  9. Contributions to robust methods of creep analysis

    International Nuclear Information System (INIS)

    Penny, B.K.

    1991-01-01

    Robust methods for the predictions of deformations and lifetimes of components operating in the creep range are presented. The ingredients used for this are well-tried numerical techniques combined with the concepts of continuum damage and so-called reference stresses. The methods described are derived in order to obtain the maximum benefit during the early stages of design where broad assessments of the influences of material choice, loadings and geometry need to be made quickly and with economical use of computers. It is also intended that the same methods will be of value during operation if estimates of damage or if exercises in life extension or inspection timing are required. (orig.)

  10. A method of uranium isotopes concentration analysis

    International Nuclear Information System (INIS)

    Lin Yuangen; Jiang Meng; Wu Changli; Duan Zhanyuan; Guo Chunying

    2010-01-01

    A basic method of uranium isotopes concentration is described in this paper. The iteration method is used to calculate the relative efficiency curve, by analyzing the characteristic γ energy spectrum of 235 U, 232 U and the daughter nuclide of 238 U, then the relative activity can be calculated, at last the uranium isotopes concentration can be worked out, and the result is validated by the experimentation. (authors)

  11. Comparative analysis of accelerogram processing methods

    International Nuclear Information System (INIS)

    Goula, X.; Mohammadioun, B.

    1986-01-01

    The work described here inafter is a short development of an on-going research project, concerning high-quality processing of strong-motion recordings of earthquakes. Several processing procedures have been tested, applied to synthetic signals simulating ground-motion designed for this purpose. The methods of correction operating in the time domain are seen to be strongly dependent upon the sampling rate. Two methods of low-frequency filtering followed by an integration of accelerations yielded satisfactory results [fr

  12. General method of quantitative spectrographic analysis

    International Nuclear Information System (INIS)

    Capdevila, C.; Roca, M.

    1966-01-01

    A spectrographic method was developed to determine 23 elements in a wide range of concentrations; the method can be applied to metallic or refractory samples. Previous melting with lithium tetraborate and germanium oxide is done in order to avoid the influence of matrix composition and crystalline structure. Germanium oxide is also employed as internal standard. The resulting beads ar mixed with graphite powder (1:1) and excited in a 10 amperes direct current arc. (Author) 12 refs

  13. AVIS: analysis method for document coherence

    International Nuclear Information System (INIS)

    Henry, J.Y.; Elsensohn, O.

    1994-06-01

    The present document intends to give a short insight into AVIS, a method which permits to verify the quality of technical documents. The paper includes the presentation of the applied approach based on the K.O.D. method, the definition of quality criteria of a technical document, as well as a description of the means of valuating these criteria. (authors). 9 refs., 2 figs

  14. Analysis of methods for quantitative renography

    International Nuclear Information System (INIS)

    Archambaud, F.; Maksud, P.; Prigent, A.; Perrin-Fayolle, O.

    1995-01-01

    This article reviews the main methods using renography to estimate renal perfusion indices and to quantify differential and global renal function. The review addresses the pathophysiological significance of estimated parameters according to the underlying models and the choice of the radiopharmaceutical. The dependence of these parameters on the region of interest characteristics and on the methods of background and attenuation corrections are surveyed. Some current recommendations are proposed. (authors). 66 refs., 8 figs

  15. Electromagnetic modeling method for eddy current signal analysis

    International Nuclear Information System (INIS)

    Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

    2004-10-01

    An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

  16. The ethnographic method and its relationship with the domain analysis

    Directory of Open Access Journals (Sweden)

    Manuel Alejandro Romero Quesada

    2016-03-01

    Full Text Available This paper analyzes the theoretical and conceptual relationship of the ethnographic method with domain analysis. A documentary analysis was performed, exploring the categories of domain analysis and ethnographic method.It was obtained as a result: the analysis of the points of contact between domain analysis and the ethnographic method from an epistemological, methodological and procedural terms. It is concluded that the ethnographic method is an important research tool to scan the turbulent socio-cultural scenarios that occur within discursive communities that constitute the domains of knowledge.

  17. Methods of Fourier analysis and approximation theory

    CERN Document Server

    Tikhonov, Sergey

    2016-01-01

    Different facets of interplay between harmonic analysis and approximation theory are covered in this volume. The topics included are Fourier analysis, function spaces, optimization theory, partial differential equations, and their links to modern developments in the approximation theory. The articles of this collection were originated from two events. The first event took place during the 9th ISAAC Congress in Krakow, Poland, 5th-9th August 2013, at the section “Approximation Theory and Fourier Analysis”. The second event was the conference on Fourier Analysis and Approximation Theory in the Centre de Recerca Matemàtica (CRM), Barcelona, during 4th-8th November 2013, organized by the editors of this volume. All articles selected to be part of this collection were carefully reviewed.

  18. A catalog of automated analysis methods for enterprise models.

    Science.gov (United States)

    Florez, Hector; Sánchez, Mario; Villalobos, Jorge

    2016-01-01

    Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Game data analysis tools and methods

    CERN Document Server

    Coupart, Thibault

    2013-01-01

    This book features an introduction to the basic theoretical tenets of data analysis from a game developer's point of view, as well as a practical guide to performing gameplay analysis on a real-world game.This book is ideal for video game developers who want to try and experiment with the game analytics approach for their own productions. It will provide a good overview of the themes you need to pay attention to, and will pave the way for success. Furthermore, the book also provides a wide range of concrete examples that will be useful for any game data analysts or scientists who want to impro

  5. Wavelet methods in mathematical analysis and engineering

    CERN Document Server

    Damlamian, Alain

    2010-01-01

    This book gives a comprehensive overview of both the fundamentals of wavelet analysis and related tools, and of the most active recent developments towards applications. It offers a stateoftheart in several active areas of research where wavelet ideas, or more generally multiresolution ideas have proved particularly effective. The main applications covered are in the numerical analysis of PDEs, and signal and image processing. Recently introduced techniques such as Empirical Mode Decomposition (EMD) and new trends in the recovery of missing data, such as compressed sensing, are also presented.

  6. Future directions in shielding methods and analysis

    International Nuclear Information System (INIS)

    Goldstein, H.

    1987-01-01

    Over the nearly half century history of shielding against reactor radiation, there has been a see-saw battle between theory and measurement. During that period the capability and accuracy of calculational methods have been enormously improved. The microscopic cross sections needed as input to the theoretical computations are now also known to adequate accuracy (with certain exceptions). Nonetheless, there remain substantial classes of shielding problems not yet accessible to satisfactory computational methods, particularly where three-dimensional geometries are involved. This paper discusses promising avenues to approach such problems, especially in the light of recent and expected advances in supercomputers. In particular, it seems that Monte Carlo methods should be much more advantageous in the new computer environment than they have been in the past

  7. DETERMINISTIC METHODS USED IN FINANCIAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    MICULEAC Melania Elena

    2014-06-01

    Full Text Available The deterministic methods are those quantitative methods that have as a goal to appreciate through numerical quantification the creation and expression mechanisms of factorial and causal, influence and propagation relations of effects, where the phenomenon can be expressed through a direct functional relation of cause-effect. The functional and deterministic relations are the causal relations where at a certain value of the characteristics corresponds a well defined value of the resulting phenomenon. They can express directly the correlation between the phenomenon and the influence factors, under the form of a function-type mathematical formula.

  8. Geometrical methods for power network analysis

    Energy Technology Data Exchange (ETDEWEB)

    Bellucci, Stefano; Tiwari, Bhupendra Nath [Istituto Nazioneale di Fisica Nucleare, Frascati, Rome (Italy). Lab. Nazionali di Frascati; Gupta, Neeraj [Indian Institute of Technology, Kanpur (India). Dept. of Electrical Engineering

    2013-02-01

    Uses advanced geometrical methods to analyse power networks. Provides a self-contained and tutorial introduction. Includes a fully worked-out example for the IEEE 5 bus system. This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds. The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system. This work addresses applied mathematicians, theoretical physicists and power engineers interested in novel mathematical approaches to power network theory.

  9. Method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1972-01-01

    Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

  10. Implicitly Weighted Methods in Robust Image Analysis

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 44, č. 3 (2012), s. 449-462 ISSN 0924-9907 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robustness * high breakdown point * outlier detection * robust correlation analysis * template matching * face recognition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.767, year: 2012

  11. Mixed Methods Analysis of Enterprise Social Networks

    DEFF Research Database (Denmark)

    Behrendt, Sebastian; Richter, Alexander; Trier, Matthias

    2014-01-01

    The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate...

  12. Analysis of Two Methods to Evaluate Antioxidants

    Science.gov (United States)

    Tomasina, Florencia; Carabio, Claudio; Celano, Laura; Thomson, Leonor

    2012-01-01

    This exercise is intended to introduce undergraduate biochemistry students to the analysis of antioxidants as a biotechnological tool. In addition, some statistical resources will also be used and discussed. Antioxidants play an important metabolic role, preventing oxidative stress-mediated cell and tissue injury. Knowing the antioxidant content…

  13. Chemical aspects of nuclear methods of analysis

    International Nuclear Information System (INIS)

    1985-01-01

    This final report includes papers which fall into three general areas: development of practical pre-analysis separation techniques, uranium/thorium separation from other elements for analytical and processing operations, and theory and mechanism of separation techniques. A separate abstract was prepared for each of the 9 papers

  14. Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs.

    Science.gov (United States)

    Shiri, Fereshteh; Pirhadi, Somayeh; Ghasemi, Jahan B

    2016-03-01

    Mer receptor tyrosine kinase is a promising novel cancer therapeutic target in many human cancers, because abnormal activation of Mer has been implicated in survival signaling and chemoresistance. 3D-QSAR analyses based on alignment independent descriptors were performed on a series of 81 Mer specific tyrosine kinase inhibitors. The fractional factorial design (FFD) and the enhanced replacement method (ERM) were applied and tested as variable selection algorithms for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. The data set was split into 65 molecules as the training set and 16 compounds as the test set. All descriptors were generated by using the GRid INdependent descriptors (GRIND) approach. After variable selection, GRIND were correlated with activity values (pIC50) by PLS regression. Of the two applied variable selection methods, ERM had a noticeable improvement on the statistical parameters of PLS model, and yielded a q (2) value of 0.77, an [Formula: see text] of 0.94, and a low RMSEP value of 0.25. The GRIND information contents influencing the affinity on Mer specific tyrosine kinase were also confirmed by docking studies. In a quantum calculation study, the energy difference between HOMO and LUMO (gap) implied the high interaction of the most active molecule in the active site of the protein. In addition, the molecular electrostatic potential energy at DFT level confirmed results obtained from the molecular docking. The identified key features obtained from the molecular modeling, enabled us to design novel kinase inhibitors.

  15. Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs

    Directory of Open Access Journals (Sweden)

    Fereshteh Shiri

    2016-03-01

    Full Text Available Mer receptor tyrosine kinase is a promising novel cancer therapeutic target in many human cancers, because abnormal activation of Mer has been implicated in survival signaling and chemoresistance. 3D-QSAR analyses based on alignment independent descriptors were performed on a series of 81 Mer specific tyrosine kinase inhibitors. The fractional factorial design (FFD and the enhanced replacement method (ERM were applied and tested as variable selection algorithms for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. The data set was split into 65 molecules as the training set and 16 compounds as the test set. All descriptors were generated by using the GRid INdependent descriptors (GRIND approach. After variable selection, GRIND were correlated with activity values (pIC50 by PLS regression. Of the two applied variable selection methods, ERM had a noticeable improvement on the statistical parameters of PLS model, and yielded a q2 value of 0.77, an rpred2 of 0.94, and a low RMSEP value of 0.25. The GRIND information contents influencing the affinity on Mer specific tyrosine kinase were also confirmed by docking studies. In a quantum calculation study, the energy difference between HOMO and LUMO (gap implied the high interaction of the most active molecule in the active site of the protein. In addition, the molecular electrostatic potential energy at DFT level confirmed results obtained from the molecular docking. The identified key features obtained from the molecular modeling, enabled us to design novel kinase inhibitors.

  16. Monte Carlo method in neutron activation analysis

    International Nuclear Information System (INIS)

    Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.

    2009-01-01

    Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA

  17. An ESDIRK Method with Sensitivity Analysis Capabilities

    DEFF Research Database (Denmark)

    Kristensen, Morten Rode; Jørgensen, John Bagterp; Thomsen, Per Grove

    2004-01-01

    of the sensitivity equations. A key feature is the reuse of information already computed for the state integration, hereby minimizing the extra effort required for sensitivity integration. Through case studies the new algorithm is compared to an extrapolation method and to the more established BDF based approaches...

  18. Statistical methods for astronomical data analysis

    CERN Document Server

    Chattopadhyay, Asis Kumar

    2014-01-01

    This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...

  19. comparison of elastic-plastic FE method and engineering method for RPV fracture mechanics analysis

    International Nuclear Information System (INIS)

    Sun Yingxue; Zheng Bin; Zhang Fenggang

    2009-01-01

    This paper described the FE analysis of elastic-plastic fracture mechanics for a crack in RPV belt line using ABAQUS code. It calculated and evaluated the stress intensity factor and J integral of crack under PTS transients. The result is also compared with that by engineering analysis method. It shows that the results using engineering analysis method is a little larger than the results using FE analysis of 3D elastic-plastic fracture mechanics, thus the engineering analysis method is conservative than the elastic-plastic fracture mechanics method. (authors)

  20. Robustness analysis method for orbit control

    Science.gov (United States)

    Zhang, Jingrui; Yang, Keying; Qi, Rui; Zhao, Shuge; Li, Yanyan

    2017-08-01

    Satellite orbits require periodical maintenance due to the presence of perturbations. However, random errors caused by inaccurate orbit determination and thrust implementation may lead to failure of the orbit control strategy. Therefore, it is necessary to analyze the robustness of the orbit control methods. Feasible strategies which are tolerant to errors of a certain magnitude can be developed to perform reliable orbit control for the satellite. In this paper, first, the orbital dynamic model is formulated by Gauss' form of the planetary equation using the mean orbit elements; the atmospheric drag and the Earth's non-spherical perturbations are taken into consideration in this model. Second, an impulsive control strategy employing the differential correction algorithm is developed to maintain the satellite trajectory parameters in given ranges. Finally, the robustness of the impulsive control method is analyzed through Monte Carlo simulations while taking orbit determination error and thrust error into account.

  1. Updated Methods for Seed Shape Analysis

    Directory of Open Access Journals (Sweden)

    Emilio Cervantes

    2016-01-01

    Full Text Available Morphological variation in seed characters includes differences in seed size and shape. Seed shape is an important trait in plant identification and classification. In addition it has agronomic importance because it reflects genetic, physiological, and ecological components and affects yield, quality, and market price. The use of digital technologies, together with development of quantification and modeling methods, allows a better description of seed shape. Image processing systems are used in the automatic determination of seed size and shape, becoming a basic tool in the study of diversity. Seed shape is determined by a variety of indexes (circularity, roundness, and J index. The comparison of the seed images to a geometrical figure (circle, cardioid, ellipse, ellipsoid, etc. provides a precise quantification of shape. The methods of shape quantification based on these models are useful for an accurate description allowing to compare between genotypes or along developmental phases as well as to establish the level of variation in different sets of seeds.

  2. Transform and filtration methods in fluctuation analysis

    International Nuclear Information System (INIS)

    Saxe, R.F.

    1976-01-01

    Digitized fluctuation signals from an ex-core ion-chamber of a PWR were analysed to produce a Power Spectral Density, (PSD), curve by two means: (1) by digital filter techniques and (2) by a Fast Fourier Transform program. For both these methods, the effects of the precision of the input data were investigated and it is shown that reasonably good PSD curves may be obtained using very poor input precision. (author)

  3. Cementation Analysis by Eddy Current Method

    OpenAIRE

    M. Zergoug; H. Oubouchou; N. Amimeur

    2009-01-01

    Increase the hardness, the endurance and the life time of material can be realised by surface treatments and remetallings, the electromagnetic properties of steels depend on their composition, their microstructures and constraints applied. We can use the electric and magnetic parameters to evaluate their microstructure. The object of this work is the characterization of cementation by the non-destructive methods and the determination of physicochemical parameters. Samples of low carbon tenor ...

  4. 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.

  5. A method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1971-01-01

    A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

  6. Digital methods for mediated discourse analysis

    DEFF Research Database (Denmark)

    Kjær, Malene; Larsen, Malene Charlotte

    2015-01-01

    , restrictions or privately mediated settings. Having used mediated discourse analysis (Scollon 2002, Scollon & Scollon, 2004) as a framework in two different research projects, we show how the framework, in correlation with digital resources for data gathering, provides new understandings of 1) the daily......In this paper we discuss methodological strategies for collecting multimodal data using digital resources. The aim is to show how digital resources can provide ethnographic insights into mediated actions (Scollon, 2002) that can otherwise be difficult to observe or engage in, due to, for instance......) and online questionnaire data in order to capture mediated actions and discourses in practice....

  7. Chemical analysis of cyanide in cyanidation process: review of methods

    International Nuclear Information System (INIS)

    Nova-Alonso, F.; Elorza-Rodriguez, E.; Uribe-Salas, A.; Perez-Garibay, R.

    2007-01-01

    Cyanidation, the world wide method for precious metals recovery, the chemical analysis of cyanide, is a very important, but complex operation. Cyanide can be present forming different species, each of them with different stability, toxicity, analysis method and elimination technique. For cyanide analysis, there exists a wide selection of analytical methods but most of them present difficulties because of the interference of species present in the solution. This paper presents the different available methods for chemical analysis of cyanide: titration, specific electrode and distillation, giving special emphasis on the interferences problem, with the aim of helping in the interpretation of the results. (Author)

  8. Risk uncertainty analysis methods for NUREG-1150

    International Nuclear Information System (INIS)

    Benjamin, A.S.; Boyd, G.J.

    1987-01-01

    Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives

  9. Proposing alerts for pre and pro-haptens (QSAR2016) ...

    Science.gov (United States)

    Predictive testing to identify and characterise substances for their skin sensitisation potential has historically been based on animal tests such as the Local Lymph Node Assay (LLNA). In recent years, regulations in the cosmetics and chemicals sectors has provided a strong impetus to develop and evaluate non-animal alternative methods. The 3 test methods that have undergone extensive development and validation are the direct peptide reactivity assay (DPRA), the KeratinoSensTM and the human Cell Line Activation Test (h-CLAT). Whilst these methods have been shown to perform relatively well in predicting LLNA results (accuracy ~ 80%), a particular concern that has been raised is their ability to predict chemicals that need to be activated to act as sensitisers (either abiotically on the skin (pre-hapten) or metabolically in the skin (pro-hapten)). This study reviewed an EURL ECVAM dataset containing 271 substances for which information was available in the LLNA and for one or more of the three non-animal test methods. The chemical structures of the substances were inspected and each assigned to a reaction mechanistic domain. Fifty-three substances were expected to require activation. Plausible reaction pathways were considered for each of the substances from which three structural alerts were hypothesised: autoxidation to hydroperoxides, aromatic ortho and para-diamino or di phenol derivatives, and aromatic meta-diamino/hydroxy derivatives. For each alert, the av

  10. Paired comparisons analysis: an axiomatic approach to ranking methods

    NARCIS (Netherlands)

    Gonzalez-Diaz, J.; Hendrickx, Ruud; Lohmann, E.R.M.A.

    2014-01-01

    In this paper we present an axiomatic analysis of several ranking methods for general tournaments. We find that the ranking method obtained by applying maximum likelihood to the (Zermelo-)Bradley-Terry model, the most common method in statistics and psychology, is one of the ranking methods that

  11. Analysis of Vibration Diagnostics Methods for Induction Motors

    Directory of Open Access Journals (Sweden)

    A. P. Kalinov

    2012-01-01

    Full Text Available The paper presents an analysis of existing vibration diagnostics methods. In order to evaluate an efficiency of method application the following criteria have been proposed: volume of input data required for establishing diagnosis, data content, software and hardware level, execution time for vibration diagnostics. According to the mentioned criteria a classification of vibration diagnostics methods for determination of their advantages and disadvantages, search for their development and improvement has been presented in paper. The paper contains a comparative estimation of methods in accordance with the proposed  criteria. According to this estimation the most efficient methods are a spectral analysis and spectral analysis of the vibration signal envelope.

  12. Molten Salt Breeder Reactor Analysis Methods

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jinsu; Jeong, Yongjin; Lee, Deokjung [Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)

    2015-05-15

    Utilizing the uranium-thorium fuel cycle shows considerable potential for the possibility of MSR. The concept of MSBR should be revised because of molten salt reactor's advantage such as outstanding neutron economy, possibility of continuous online reprocessing and refueling, a high level of inherent safety, and economic benefit by keeping off the fuel fabrication process. For the development of MSR research, this paper provides the MSBR single-cell, two-cell and whole core model for computer code input, and several calculation results including depletion calculation of each models. The calculations are carried out by using MCNP6, a Monte Carlo computer code, which has CINDER90 for depletion calculation using ENDF-VII nuclear data. From the calculation results of various reactor design parameters, the temperature coefficients are all negative at the initial state and MTC becomes positive at the equilibrium state. From the results of core rod worth, the graphite control rod alone cannot makes the core subcritical at initial state. But the equilibrium state, the core can be made subcritical state only by graphite control rods. Through the comparison of the results of each models, the two-cell method can represent the MSBR core model more accurately with a little more computational resources than the single-cell method. Many of the thermal spectrum MSR have adopted a multi-region single-fluid strategy.

  13. 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....

  14. Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling.

    Science.gov (United States)

    Kumar, Raj; Son, Minky; Bavi, Rohit; Lee, Yuno; Park, Chanin; Arulalapperumal, Venkatesh; Cao, Guang Ping; Kim, Hyong-ha; Suh, Jung-keun; Kim, Yong-seong; Kwon, Yong Jung; Lee, Keun Woo

    2015-08-01

    Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.

  15. 3D-QSAR studies on CCR2B receptor antagonists: Insight into the structural requirements of (R-3-aminopyrrolidine series of molecules based on CoMFA/CoMSIA models

    Directory of Open Access Journals (Sweden)

    Swetha Gade

    2012-01-01

    Full Text Available Objective: Monocyte chemo attractant protein-1 (MCP-1 is a member of the CC-chemokine family and it selectively recruits leukocytes from the circulation to the site of inflammation through binding with the chemotactic cytokine receptor 2B (CCR2B. The recruitment and activation of selected populations of leukocytes is a key feature in a variety of inflammatory conditions. Thus MCP-1 receptor antagonist represents an attractive target for drug discovery. To understand the structural requirements that will lead to enhanced inhibitory potencies, we have carried out 3D-QSAR (quantitative structure-activity relationship studies on (R-3-aminopyrrolidine series of molecules as CCR2B receptor antagonists. Materials and Methods: Comparative molecular field analysis (CoMFA and comparative molecular similarity indices analysis (CoMSIA were performed on a series of (R-3-aminopyrrolidine derivatives as antagonists of CCR2B receptor with Sybyl 6.7v. Results: We have derived statistically significant model from 37 molecules and validated it against an external test set of 13 compounds. The CoMFA model yielded a leave one out r 2 (r 2 loo of 0.847, non-cross-validated r 2 (r 2 ncv of 0.977, F value of 267.930, and bootstrapped r 2 (r 2 bs of 0.988. We have derived the standard error of prediction value of 0.367, standard error of estimate 0.141, and a reliable external predictivity, with a predictive r 2 (r 2 pred of 0.673. While the CoMSIA model yielded an r 2 loo of 0.719, r 2 ncv of 0.964,F value of 135.666, r 2 bs of 0.975, standard error of prediction of 0.512, standard error of estimate of 0.180, and an external predictivity with an r 2 pred of 0.611. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r 2 pred, based on the mean activity of test set compounds can accurately estimate external predictivity. Conclusion: The QSAR model gave satisfactory statistical results in terms of q 2 and r 2

  16. Simplified piping analysis methods with inelastic supports

    International Nuclear Information System (INIS)

    Lin, C.W.; Romanko, A.D.

    1986-01-01

    Energy absorbing supports (EAS) which contain x-shaped plates or dampers with heavy viscous fluid can absorb a large amount of energy during vibratory motions. The response of piping systems supported by these types of energy absorbing devices can be markedly reduced as compared with ordinary supports using rigid rods, hangers or snubbers. In this paper, a simple multiple support response spectrum technique is presented, which would allow the energy dissipation nature of the EAS be factored in the piping response calculation. In the meantime, the effect of lower system frequencies due to the reduced support stiffness from local yielding is also included in the analysis. Numerical results obtained show that this technique is more conservative than the time history solution by an acceptable and realistic margin; and it has less than 10 percent of the computation cost

  17. Surface analysis methods in materials science

    CERN Document Server

    Sexton, Brett; Smart, Roger

    1992-01-01

    The idea for this book stemmed from a remark by Philip Jennings of Murdoch University in a discussion session following a regular meeting of the Australian Surface Science group. He observed that a text on surface analysis and applica­ tions to materials suitable for final year undergraduate and postgraduate science students was not currently available. Furthermore, the members of the Australian Surface Science group had the research experience and range of coverage of sur­ face analytical techniques and applications to provide a text for this purpose. A of techniques and applications to be included was agreed at that meeting. The list intended readership of the book has been broadened since the early discussions, particularly to encompass industrial users, but there has been no significant alter­ ation in content. The editors, in consultation with the contributors, have agreed that the book should be prepared for four major groups of readers: - senior undergraduate students in chemistry, physics, metallur...

  18. Radiation analysis devices, radiation analysis methods, and articles of manufacture

    Science.gov (United States)

    Roybal, Lyle Gene

    2010-06-08

    Radiation analysis devices include circuitry configured to determine respective radiation count data for a plurality of sections of an area of interest and combine the radiation count data of individual of sections to determine whether a selected radioactive material is present in the area of interest. An amount of the radiation count data for an individual section is insufficient to determine whether the selected radioactive material is present in the individual section. An article of manufacture includes media comprising programming configured to cause processing circuitry to perform processing comprising determining one or more correction factors based on a calibration of a radiation analysis device, measuring radiation received by the radiation analysis device using the one or more correction factors, and presenting information relating to an amount of radiation measured by the radiation analysis device having one of a plurality of specified radiation energy levels of a range of interest.

  19. IMP: Integrated method for power analysis

    Energy Technology Data Exchange (ETDEWEB)

    1989-03-01

    An integrated, easy to use, economical package of microcomputer programs has been developed which can be used by small hydro developers to evaluate potential sites for small scale hydroelectric plants in British Columbia. The programs enable evaluation of sites located far from the nearest stream gauging station, for which streamflow data are not available. For each of the province's 6 hydrologic regions, a streamflow record for one small watershed is provided in the data base. The program can then be used to generate synthetic streamflow records and to compare results obtained by the modelling procedure with the actual data. The program can also be used to explore the significance of modelling parameters and to develop a detailed appreciation for the accuracy which can be obtained under various circumstances. The components of the program are an atmospheric model of precipitation; a watershed model that will generate a continuous series of streamflow data, based on information from the atmospheric model; a flood frequency analysis system that uses site-specific topographic data plus information from the atmospheric model to generate a flood frequency curve; a hydroelectric power simulation program which determines daily energy output for a run-of-river or reservoir storage site based on selected generation facilities and the time series generated in the watershed model; and a graphic analysis package that provides direct visualization of data and modelling results. This report contains a description of the programs, a user guide, the theory behind the model, the modelling methodology, and results from a workshop that reviewed the program package. 32 refs., 16 figs., 18 tabs.

  20. Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

    Science.gov (United States)

    Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

    2013-01-01

    The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  1. Standard methods for analysis of phosphorus-32

    International Nuclear Information System (INIS)

    Anon.

    1975-01-01

    Methods are described for the determination of the radiochemical purity and the absolute disintegration rate of 32 P radioisotope preparations. The 32 P activity is determined by β counting, and other low-energy β radioactive contaminants are determined by aluminum-absorption curve data. Any γ-radioactive contaminants are determined by γ counting. Routine chemical testing is used to establish the chemical characteristics. The presence or absence of heavy metals is established by spot tests; free acid is determined by use of a pH meter; total solids are determined gravimetrically by evaporation and ignition at a temperature sufficient to evaporate the mineral acids, HCl and HNO 3 ; and nonvolatile matter, defined as that material which does not evaporate or ignite at a temperature sufficient to convert C to CO or CO 2 , is determined gravimetrically after such ignition

  2. 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 ...

  3. Stochastic seismic floor response analysis method for various damping systems

    International Nuclear Information System (INIS)

    Kitada, Y.; Hattori, K.; Ogata, M.; Kanda, J.

    1991-01-01

    A study using the stochastic seismic response analysis method which is applicable for the estimation of floor response spectra is carried out. It is pointed out as a shortcoming in this stochastic seismic response analysis method, that the method tends to overestimate floor response spectra for low damping systems, e.g. 1% of the critical damping ratio. An investigation on the cause of the shortcoming is carried out and a number of improvements in this method were also made to the original method by taking correlation of successive peaks in a response time history into account. The application of the improved method to a typical BWR reactor building is carried out. The resultant floor response spectra are compared with those obtained by deterministic time history analysis. Floor response spectra estimated by the improved method consistently cover the response spectra obtained by the time history analysis for various damping ratios. (orig.)

  4. CHAPTER 7. BERYLLIUM ANALYSIS BY NON-PLASMA BASED METHODS

    Energy Technology Data Exchange (ETDEWEB)

    Ekechukwu, A

    2009-04-20

    The most common method of analysis for beryllium is inductively coupled plasma atomic emission spectrometry (ICP-AES). This method, along with inductively coupled plasma mass spectrometry (ICP-MS), is discussed in Chapter 6. However, other methods exist and have been used for different applications. These methods include spectroscopic, chromatographic, colorimetric, and electrochemical. This chapter provides an overview of beryllium analysis methods other than plasma spectrometry (inductively coupled plasma atomic emission spectrometry or mass spectrometry). The basic methods, detection limits and interferences are described. Specific applications from the literature are also presented.

  5. RESULTS OF THE QUESTIONNAIRE: ANALYSIS METHODS

    CERN Multimedia

    Staff Association

    2014-01-01

    Five-yearly review of employment conditions   Article S V 1.02 of our Staff Rules states that the CERN “Council shall periodically review and determine the financial and social conditions of the members of the personnel. These periodic reviews shall consist of a five-yearly general review of financial and social conditions;” […] “following methods […] specified in § I of Annex A 1”. Then, turning to the relevant part in Annex A 1, we read that “The purpose of the five-yearly review is to ensure that the financial and social conditions offered by the Organization allow it to recruit and retain the staff members required for the execution of its mission from all its Member States. […] these staff members must be of the highest competence and integrity.” And for the menu of such a review we have: “The five-yearly review must include basic salaries and may include any other financial or soc...

  6. Vulnerability analysis methods for road networks

    Science.gov (United States)

    Bíl, Michal; Vodák, Rostislav; Kubeček, Jan; Rebok, Tomáš; Svoboda, Tomáš

    2014-05-01

    Road networks rank among the most important lifelines of modern society. They can be damaged by either random or intentional events. Roads are also often affected by natural hazards, the impacts of which are both direct and indirect. Whereas direct impacts (e.g. roads damaged by a landslide or due to flooding) are localized in close proximity to the natural hazard occurrence, the indirect impacts can entail widespread service disabilities and considerable travel delays. The change in flows in the network may affect the population living far from the places originally impacted by the natural disaster. These effects are primarily possible due to the intrinsic nature of this system. The consequences and extent of the indirect costs also depend on the set of road links which were damaged, because the road links differ in terms of their importance. The more robust (interconnected) the road network is, the less time is usually needed to secure the serviceability of an area hit by a disaster. These kinds of networks also demonstrate a higher degree of resilience. Evaluating road network structures is therefore essential in any type of vulnerability and resilience analysis. There are a range of approaches used for evaluation of the vulnerability of a network and for identification of the weakest road links. Only few of them are, however, capable of simulating the impacts of the simultaneous closure of numerous links, which often occurs during a disaster. The primary problem is that in the case of a disaster, which usually has a large regional extent, the road network may remain disconnected. The majority of the commonly used indices use direct computation of the shortest paths or time between OD (origin - destination) pairs and therefore cannot be applied when the network breaks up into two or more components. Since extensive break-ups often occur in cases of major disasters, it is important to study the network vulnerability in these cases as well, so that appropriate

  7. An advanced probabilistic structural analysis method for implicit performance functions

    Science.gov (United States)

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

    1989-01-01

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

  8. 21 CFR 2.19 - Methods of analysis.

    Science.gov (United States)

    2010-04-01

    ... Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL GENERAL ADMINISTRATIVE RULINGS AND DECISIONS General Provisions § 2.19 Methods of analysis. Where the method of analysis... issues of the “Journal of the Association of Official Analytical Chemists”), which are incorporated by...

  9. Basic methods of isotope analysis; Osnovnye metody analiza izotopov

    Energy Technology Data Exchange (ETDEWEB)

    Ochkin, A V; Rozenkevich, M B

    2000-07-01

    The bases of the most applied methods of the isotope analysis are briefly presented. The possibilities and analytical characteristics of the mass-spectrometric, spectral, radiochemical and special methods of the isotope analysis, including application of the magnetic resonance, chromatography and refractometry, are considered.

  10. Nonlinear nonstationary analysis with the finite element method

    International Nuclear Information System (INIS)

    Vaz, L.E.

    1981-01-01

    In this paper, after some introductory remarks on numerical methods for the integration of initial value problems, the applicability of the finite element method for transient diffusion analysis as well as dynamic and inelastic analysis is discussed, and some examples are presented. (RW) [de

  11. Probabilistic structural analysis methods for space transportation propulsion systems

    Science.gov (United States)

    Chamis, C. C.; Moore, N.; Anis, C.; Newell, J.; Nagpal, V.; Singhal, S.

    1991-01-01

    Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .

  12. QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity

    Directory of Open Access Journals (Sweden)

    Marjan Vračko

    2010-03-01

    Full Text Available Reproductive toxicity is an important regulatory endpoint, which is required in registration procedures of chemicals used for different purposes (for example pesticides. The in vivo tests are expensive, time consuming and require large numbers of animals, which must be sacrificed. Therefore an effort is ongoing to develop alternative In vitro and in silico methods to evaluate reproductive toxicity. In this review we describe some modeling approaches. In the first example we describe the CAESAR model for prediction of reproductive toxicity; the second example shows a classification model for endocrine disruption potential based on counter propagation artificial neural networks; the third example shows a modeling of relative binding affinity to rat estrogen receptor, and the fourth one shows a receptor dependent modeling experiment.

  13. Alternative methods for the seismic analysis of piping systems

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    This document is a review of 12 methods and criteria for the seismic analysis of piping systems. Each of the twelve chapters in this document cover the important technical aspects of a given method. The technical aspects presented are those the Subcommittee on Dynamic Stress Criteria believe important to the application of the method, and should not be considered as a positive or negative endorsement for any of the methods. There are many variables in an analysis of a piping system that can influence the selection of the analysis method and criteria to be applied. These variable include system configuration, technical issues, precedent, licensing considerations, and regulatory acceptance. They must all be considered in selecting the appropriate seismic analysis method and criteria. This is relevant for nuclear power plants

  14. Method and procedure of fatigue analysis for nuclear equipment

    International Nuclear Information System (INIS)

    Wen Jing; Fang Yonggang; Lu Yan; Zhang Yue; Sun Zaozhan; Zou Mingzhong

    2014-01-01

    As an example, the fatigue analysis for the upper head of the pressurizer in one NPP was carried out by using ANSYS, a finite element method analysis software. According to RCC-M code, only two kinds of typical transients of temperature and pressure were considered in the fatigue analysis. Meanwhile, the influence of earthquake was taken into account. The method and procedure of fatigue analysis for nuclear safety equipment were described in detail. This paper provides a reference for fatigue analysis and assessment of nuclear safety grade equipment and pipe. (authors)

  15. Participant Interaction in Asynchronous Learning Environments: Evaluating Interaction Analysis Methods

    Science.gov (United States)

    Blanchette, Judith

    2012-01-01

    The purpose of this empirical study was to determine the extent to which three different objective analytical methods--sequence analysis, surface cohesion analysis, and lexical cohesion analysis--can most accurately identify specific characteristics of online interaction. Statistically significant differences were found in all points of…

  16. Use of some nuclear methods for materials analysis

    International Nuclear Information System (INIS)

    Habbani, Farouk

    1994-01-01

    A review is given about the use of two nuclear-related analytical methods, namely: X-ray fluorescence (XRF) and neutron activation analysis (NAA), for the determination of elemental composition of various materials. Special emphasis is given to the use of XRF for the analysis of geological samples, and NAA for the analysis of food - stuffs for their protein content. (Author)

  17. direct method of analysis of an isotropic rectangular plate direct

    African Journals Online (AJOL)

    eobe

    This work evaluates the static analysis of an isotropic rectangular plate with various the static analysis ... method according to Ritz is used to obtain the total potential energy of the plate by employing the used to ..... for rectangular plates analysis, as the behavior of the ... results obtained by previous research work that used.

  18. Nano-QSAR: Genotoxicity of Multi-Walled Carbon Nanotubes

    International Nuclear Information System (INIS)

    Toropova, A. P.; Toropov, A. A.; Rallo, R.; Leszczynska, D.; Leszczynski, J.

    2016-01-01

    The study was carried out to develop an efficient approach for prediction the genotoxicity of carbon nano tubes. The experimental data on the bacterial reverse mutation test (TA100) on multi-walled carbon nano tubes was collected from the literature and examined as an endpoint. By means of the optimal descriptors calculated with the Monte Carlo method a mathematical model of the endpoint was built up. The model is represented by a function of: (i) dose (μg/plate); (ii) metabolic activation (i.e. with S9 mix or without S9 mix); and (iii) two types of multi-walled carbon nano tubes. The above listed conditions were represented by so-called quasi-SMILES. Simplified molecular input-line entry system (SMILES) is a tool for representation of molecular structure. The quasi-SMILES is a tool to represent physicochemical and / or biochemical conditions for building up a predictive model. Thus, instead of well-known paradigm of predictive modeling “endpoint is a mathematical function of molecular structure” a fresh paradigm “endpoint is a mathematical function of available eclectic data (conditions) is suggested.

  19. Analysis and study on core power capability with margin method

    International Nuclear Information System (INIS)

    Liu Tongxian; Wu Lei; Yu Yingrui; Zhou Jinman

    2015-01-01

    Core power capability analysis focuses on the power distribution control of reactor within the given mode of operation, for the purpose of defining the allowed normal operating space so that Condition Ⅰ maneuvering flexibility is maintained and Condition Ⅱ occurrences are adequately protected by the reactor protection system. For the traditional core power capability analysis methods, such as synthesis method or advanced three dimension method, usually calculate the key safety parameters of the power distribution, and then verify that these parameters meet the design criteria. For PWR with on-line power distribution monitoring system, core power capability analysis calculates the most power level which just meets the design criteria. On the base of 3D FAC method of Westinghouse, the calculation model of core power capability analysis with margin method is introduced to provide reference for engineers. The core power capability analysis of specific burnup of Sanmen NPP is performed with the margin method. The results demonstrate the rationality of the margin method. The calculation model of the margin method not only helps engineers to master the core power capability analysis for AP1000, but also provides reference for engineers for core power capability analysis of other PWR with on-line power distribution monitoring system. (authors)

  20. 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.