scholarly journals Evaluation of phenylethylamine type entactogens and their metabolites relevant to ecotoxicology – a QSAR study

2019 ◽  
Vol 69 (4) ◽  
pp. 563-584 ◽  
Author(s):  
Milena Jadrijević-Mladar Takač ◽  
Joao Daniel Casimiro Magina ◽  
Tin Takač

Abstract The impact of the selected entactogens and their o-quinone metabolites on the environment was explored in QSAR studies by the use of predicted molecular descriptors, ADMET properties and environmental toxicity parameters, i.e., acute toxicity in Tetrahymena pyriformis (TOX_ATTP) expressed as Th_pyr_pIGC50/mmol L−1, acute toxicity in Pimephales promelas, the fathead minnow (TOX_FHM) expressed as Minnow LC50/mg L−1, the acute toxicity in Daphnia magna (TOX_DM) expressed as Daphnia LC50/mg L−1 and bioconcentration factor (BCF). The formation of corresponding o-quinones via benzo-dioxo-lone ring, O-demethylenation was predicted as the main metabolic pathway for all entactogens except for 1-(2,2-difluorobenzo[d][1,3]dioxol-5-yl)propan-2-amine (DiFMDA). The least favourable ADMET profile was revealed for N-(1-(benzo[d][1,3]dioxol-5-yl)propan-2-yl)-O-methylhydroxylamine (MDMEO). QSAR studies revealed significant linear correlations between MlogP of entactogens and MlogP of o-quinone metabolites (R = 0.99), and Th_pyr_pIGC50/mmol L−1 (R = 0.94), also their MlogPs with Minnow_LC50/mg L−1 (R = 0.80 and R = 0.78), BCF (R = 0.86 and R = 0.82) and percentage of o-quinones’ yields (R = 0.73 and R = 0.80). Entactogens were predicted as non-biodegradable molecules, whereas the majority of their o-quinones were biodegradable.

2013 ◽  
Vol 295-298 ◽  
pp. 95-99
Author(s):  
Hong Xia Liu ◽  
Guo Hua Zhao

3D-QSAR studies of halogenated phenols screening for acute toxicity were performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Groups’ data has been modeled to obtain an average estimate and a predictive value for ranking and screening purposes. CoMFA and CoMSIA models have given cross-validation regression coefficient (q2) values of more than 0.80 and correlation coefficient (R2) value of more than 0. 96, which validated for their prediction, could be applied to predict unavailable data.


2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Mirko Andreja Borisov

Climate change conditions a wide range of impacts such as the impact on weather, but also on ecosystems and biodiversity, agriculture and forestry, human health, hydrological regime and energy. In addition to global warming, local factors affecting climate change are being considered. Presentation and analysis of the situation was carried out using geoinformation technologies (radar recording, remote detection, digital terrain modeling, cartographic visualization and geostatistics). This paper describes methods and use of statistical indicators such as LST, NDVI and linear correlations from which it can be concluded that accelerated construction and global warming had an impact on climate change in period from 1987 to 2018 in the area of Vojvodina – Republic of Serbia. Also, using the global SRTM DEM, it is shown how the temperature behaves based on altitude change. Conclusions and possible consequences in nature and society were derived.


2017 ◽  
pp. 1339-1366
Author(s):  
Valeria V. Kleandrova ◽  
Feng Luan ◽  
Alejandro Speck-Planche ◽  
M. Natália D. S. Cordeiro

Nanotechnology is a newly emerging field, posing substantial impacts on society, economy, and the environment. In recent years, the development of nanotechnology has led to the design and large-scale production of many new materials and devices with a vast range of applications. However, along with the benefits, the use of nanomaterials raises many questions and generates concerns due to the possible health-risks and environmental impacts. This chapter provides an overview of the Quantitative Structure-Activity Relationships (QSAR) studies performed so far towards predicting nanoparticles' environmental toxicity. Recent progresses on the application of these modeling studies are additionally pointed out. Special emphasis is given to the setup of a QSAR perturbation-based model for the assessment of ecotoxic effects of nanoparticles in diverse conditions. Finally, ongoing challenges that may lead to new and exciting directions for QSAR modeling are discussed.


2014 ◽  
Vol 79 (9) ◽  
pp. 1111-1125 ◽  
Author(s):  
Dan-Dan Wang ◽  
Lin-Lin Feng ◽  
Guang-Yu He ◽  
Hai-Qun Chen

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.


Author(s):  
Christine L. Russom ◽  
Steven P. Bradbury ◽  
Steven J. Broderius ◽  
Dean E. Hammermeister ◽  
Robert A. Drummond

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