Toxicity of binary mixtures of pesticides and pharmaceuticals toward Vibrio fischeri: Assessment by quantitative structure-activity relationships

Bureš, Marija Sigurnjak; Ukić, Šime; Cvetnić, Matija; Prevarić, Viktorija; Markić, Marinko; Rogošić, Marko; Kušić, Hrvoje; Bolanča, Tomislav

doi:10.1016/j.envpol.2020.115885

Cited by 15 publications

(2 citation statements)

References 55 publications

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“…In the statistical procedure, we approached the development of the QSAR model using the obtained TEAC values and calculated descriptors. Data splitting to create training and the test set was performed using the rational splitting method based on activity value, to cover the whole range of TEAC values [ 22 ]. As a result, one- to eight-variable models were obtained.…”

Section: Resultsmentioning

confidence: 99%

Antioxidant Activity of Pharmaceuticals: Predictive QSAR Modeling for Potential Therapeutic Strategy

et al. 2022

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Since oxidative stress has been linked to several pathological conditions and diseases, drugs with additional antioxidant activity can be beneficial in the treatment of these diseases. Therefore, this study takes a new look at the antioxidant activity of frequently prescribed drugs using the HPLC-DPPH method. The antioxidative activity expressed as the TEAC value of 82 drugs was successfully determined and is discussed in this work. Using the obtained values, the QSAR model was developed to predict the TEAC based on the selected molecular descriptors. The results of QSAR modeling showed that four- and seven-variable models had the best potential for TEAC prediction. Looking at the statistical parameters of each model, the four-variable model was superior to seven-variable. The final model showed good predicting power (r = 0.927) considering the selected descriptors, implying that it can be used as a fast and economically acceptable evaluation of antioxidative activity. The advantage of such model is its ability to predict the antioxidative activity of a drug regardless of its structural diversity or therapeutic classification.

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Section: Resultsmentioning

confidence: 99%

Antioxidant Activity of Pharmaceuticals: Predictive QSAR Modeling for Potential Therapeutic Strategy

et al. 2022

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“…In most cases, the acute biological toxicity test result for V. fischeri should be expressed as effective concentrations of wastewater causing 50% inhibition of bioluminescence to V. fischeri (EC 50 ) (Yu et al 2014;Abbas et al 2018;Sigurnjak Bures et al 2021), however, due to the complicated composition of the industrial effluents (Figures 1-4), inhibition rates of bioluminescence after exposure to the samples were used in this study to represent the acute biological toxicity. This is also widely accepted for wastewater biological toxicity evaluation (Fang et al 2019;Lai et al 2021).…”

Section: Acute Biological Toxicitymentioning

confidence: 99%

Identifying influential priority of factors governing the acute biological toxicity of two kinds of industrial wastewaters

Pan

Peng³

et al. 2022

Journal of Water Reuse and Desalination

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Identifying the key parameters or components mainly contributing to the acute toxicity of wastewater would be helpful to quickly and conveniently reflect their biological toxicity. In this study, the components/parameters and biological toxicity of 64 effluent samples collected from two factories producing konjac and glass were analyzed. It was found that the two types of wastewaters were not effectively dealt with the inner technology. Moreover, the acute biological toxicity evaluated by the bioluminescence inhibition to Vibrio fischeri revealed that ∼90% of the effluents were marked as toxic with bioluminescence inhibition higher than 50%. By applying a grey relational analysis (GRA) method to investigate the influential priorities of the effluent characteristics on biological toxicity, the results demonstrated that the top four influential factors on the bioluminescence inhibition were as follows: TN ≈ SO42− > Cl− > As ≈ Hg (for konjac-manufacturing effluents) and Zn > SO42− ≈ TN > As > Cl− (for glass-producing effluents). These results would be useful for fast recognizing the biological toxicity features of industrial effluents via evaluating the most influential parameters, and helpful for reducing the biological acute toxicity to protect the downstream wastewater treatment plant from abrupt collapse.

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Ecotoxicological QSAR modeling and fate estimation of pharmaceuticals

Caliskan

Tuğcu

Önlü

et al. 2023

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

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Toxicity of binary mixtures of pesticides and pharmaceuticals toward Vibrio fischeri: Assessment by quantitative structure-activity relationships

Cited by 15 publications

References 55 publications

Antioxidant Activity of Pharmaceuticals: Predictive QSAR Modeling for Potential Therapeutic Strategy

Antioxidant Activity of Pharmaceuticals: Predictive QSAR Modeling for Potential Therapeutic Strategy

Identifying influential priority of factors governing the acute biological toxicity of two kinds of industrial wastewaters

Ecotoxicological QSAR modeling and fate estimation of pharmaceuticals

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