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1

QSAR study of amine collectors for iron ore reverse flotation

Wang Benying, Xu Xinyang, Duan Hao, Wang Xinyang

Physicochemical Problems of Mineral Processing

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2019

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Vol. 55, iss. 5

1059--1069

EN

In order to reveal the relationship between flotation behaviors of collectors and their structures, quantitative structure–activity relationship (QSAR) study about separation efficiency of quartz from hematite using amine collectors was performed. The genetic function approximation (GFA) algorithm was applied to generate the correlation models and model with acceptable R2 and Rcv2 (cross validated R-squared) correlation coefficients (R2=0.9666, Rcv2=0.9201) was developed. The model revealed that the Lowest Unoccupied Molecular Orbital (LUMO) energy of the molecule, the charge of nitrogen and the electronegativity of polar group were the major factors that affected the separation efficiency of collectors. The higher nitrogen charge, the larger electronegativity of polar group and the more positive of LUMO energy of amine collectors were, the higher separation efficiency would be.

2

Degradation mechanism study of amine collectors in Fenton process by quantitative structure-activity relationship analysis

Wang X., Liu W., Duan H., Liu W.

Physicochemical Problems of Mineral Processing

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2018

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Vol. 54, iss. 3

713--721

EN

In this study, advanced oxidation processes (AOPs), Fenton process, was applied to degrade ten amine collectors. The experimental results indicated that most of the tested amines could be removed rapidly and effectively at pH=4, while the degradation of quaternary ammonium compounds was less than others. To research the Fenton oxidation process, the degradation-rate constants of amine collectors were calculated by the pseudo-second order kinetic model, then which was used as the dependent variable to establish a quantitative structure activity relationship (QSAR) model. Meanwhile, 16 molecular structure descriptors and quantum mechanical parameters for amine collectors were simulated and analyzed by using Materials Studio software. The optimum QSAR model was established based on the partial least squares regression (PLS) method and confirmed by the statistics analysis. The model revealed that hydrogen bond acceptor (HBA) and the maximum values of electrophilic attack in C atom sites (f(-)c) were the major effect factors for the degradation-rate constants of amine collector.

3

Zastosowanie metod QSAR do określania właściwości fizykochemicznych na przykładzie izomaślanu 3-hydroksy-2,2,4-trimetylopentylu

Guziałowska-Tic J.

Przemysł Chemiczny

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2017

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T. 96, nr 8

1673--1676

PL

Porównano wyniki eksperymentalnych badań właściwości fizykochemicznych hydroksyestru HE-1 z wynikami pochodzącymi z narzędzia T.E.S.T. Stwierdzono, że narzędzie to może być wykorzystywane do określania gęstości oraz temperatury wrzenia. W tym przypadku błędy wyniosły odpowiednio 2,9 i 2,1%. W przypadku rozpuszczalności w wodzie i lepkości zgodność była niezadowalająca, a błędy wyniosły ponad 50%.

EN

D., b.p., water soly. and viscosity of the hydroxyester were detd. exptl. as well as by using a specialized computer software based on the quant. relationship between chem. structure and chem. activity to cf. the results obtained by both methods. The computer software was successfully used to det. d. and b.p. for which the relative errors were 2.9 and 2.1%, resp. In contrast, the conformity of water soly. and viscosity was not good enough and the relative errors exceeded 50%.

4

Metody QSAR jako alternatywa dla badań na zwierzętach w ocenie toksycznych i ekotoksycznych zagrożeń ze strony substancji chemicznych

Guziałowska-Tic J., Tic W. J.

Przemysł Chemiczny

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2016

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T. 95, nr 8

1475--1478

PL

Przedstawiono obecny stan wiedzy dotyczący zastosowania modeli opartych na ilościowej zależności między strukturą chemiczną i aktywnością chemiczną (QSAR) do oceny toksycznych i ekotoksycznych zagrożeń substancji chemicznych w ramach rejestracji w systemie REACH. Omówiono również zgodność pomiędzy wynikami badań wykonanymi na zwierzętach a tymi uzyskanymi przy zastosowaniu modeli QSAR.

EN

A review, with 24 refs., of methods for detn. of quanitative structure-activity relationships.

5

Toksykologia in silico – teoria i możliwości wykorzystania

Stradecka A.

Przegląd Techniczny : Gazeta Inżynierska

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2016

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nr 8

15--16

PL

Artykuł omawia metody badań toksykologicznych in silico. Opisane zostały w nim modele badań oparte na zasadzie zależności struktura-aktywność (SAR) oraz inne przykłady wykorzystania modelowania matematycznego do oceny toksyczności substancji chemicznych.

EN

The following article gives examples of in silico methods used in modern toxicology. Described are models based on structure-activity relationships (SARs) and other uses of mathematical modeling used for assessing the toxicity of the compound.

6

Structure Activity Relationships, QSAR Modeling and Drug-like calculations of TP inhibition of 1,3,4-oxadiazoline-2-thione Derivatives

Almi Z., Belaidi S., Lanez T., Tchouar N.

International Letters of Chemistry, Physics and Astronomy

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2014

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Vol. 18

113--124

EN

QSAR studies have been performed on twenty-one molecules of 1,3,4-oxadiazoline-2-thiones. The compounds used are among the most thymidine phosphorylase (TP) inhibitors. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and TP inhibition of the 1,3,4-oxadiazoline-2-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: logP, HE, Pol, MR, MV, and MW, qO1, SAG, for the TP inhibitory activity. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

7

Molecular modelling techniques in environmental research

Urniaż R. D., Rutkowska E., Jastrzębski J. P., Książek P., Rudnicka K.

Environmental Biotechnology

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2013

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Vol. 9, No. 2

39--51

EN

Over the last few decades significant increase in computational methods (in silico) was annotated. Novel methods have been developed and applied for hypothesis improvement and testing in regions of industrial, pharmaceutical and environmental research. The term in silico methods include variety of approaches. Considerable attention has been attracted to databases, data analysis tools, quantitative structure-activity relationships (QSAR), pharmacophore models, molecular docking and dynamics, pharmacokinetics and other molecular modelling techniques. In silico methods are often accompanied by experimental data, both to create the model and to test it. Such models are frequently used in the discovery and optimization of novel molecules with expected affinity to a target, the estimation of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The review summarizes briefly the applications of most common molecular modelling techniques and evaluates their application in environmental research. Additionally, this study considers computer aided methods as potential and complex tools that may serve as valuable partnership with wet-lab experiments and may provide a rational aid to minimize the cost and time of research.

8

Zastosowanie metod spektroskopowych w analizie QSAR

Kalinowska M.

LAB Laboratoria, Aparatura, Badania

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2011

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R. 16, nr 6

10-14

9

Use of cluster analysis and rough set approaches in predicting toxicity of chemicals

Dębska B.

Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk

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2001

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Nr 928

12-19

EN

The paper presented the applications of quantitive structure-activity relationships (QSAR) in environmental chemistry and toxicology. In this study, statistical and rough set methods have been applied to the development of QSAR models for estimating the acute aquatic toxicity of selected chemical compounds. Physicochemical and topostructural indices were used as properties relevant to the assessment of toxicity. These parameters have been used in the formulation of QSAR models for predicting toxicological properties. In the experimental part of the paper, results obtained in testing of ROSETTA toolkit and VVT module are presented. The rough set methodology were then used in selection and reduction the number of paramaters (chemical indexes described the selected compounds) before cluster analysis. Cluster analysis methods were used in unsupervised learning, classifying new compounds and predicting toxicity of chemicals. The results of test cases show that both give accaptable estimates for the toxicity of the compounds studied in this paper.