Quantitative Structure-Activity Relationships for the Toxicity to the Tadpole Rana japonica of Selected Phenols

Wang, X.; Dong, Yalin; Xu, Suyun; Wang, L.; Han, Sang‐Ik

doi:10.1007/s0012800082

Cited by 9 publications

(7 citation statements)

References 14 publications

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“…In addition, the presence of OH groups in nitrocompounds leads to enhancement of acidity and therefore influences toxicity. However, toxic mechanisms for nitrophenols and nitroanilines varied from polar narcosis to electrophilic reactivity as a result of the diverse amounts and positions of the nitro group on aromatic ring [59][60][61][62].…”

Section: Resultsmentioning

confidence: 99%

In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study

Gooch

Sizochenko

Rasulev

et al. 2017

Enviro Toxic and Chemistry

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The toxicity data of 90 nitroaromatic compounds related to their 50% lethal dose concentration for rats (LD50) were analyzed to develop quantitative structure-activity relationship (QSAR) models. Quantum-chemically calculated descriptors together with molecular descriptors generated by DRAGON, PaDEL, and HiT-QSAR software were utilized to build QSAR models. Quality and validity of the models were determined by internal and external validation techniques. The results show that the toxicity of nitroaromatic compounds depends on various factors, such as the number of nitro-groups, the topological state, and the presence of certain structural fragments. The developed models based on the largest (to date) dataset of nitroaromatics in vivo toxicity showed a good predictive ability. The results provide important input that could be applied in a preliminary assessment of nitroaromatic compounds' toxicity to mammals. Environ Toxicol Chem 2017;36:2227-2233. © 2017 SETAC.

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Section: Resultsmentioning

confidence: 99%

In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study

Gooch

Sizochenko

Rasulev

et al. 2017

Enviro Toxic and Chemistry

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“…Nearly 500 substances with known toxicity values to at least one of the eight selected aquatic species have been considered in this work. ,− ,− A PCA analysis of the available solutes has been done according to their SPM molecular descriptors . In this way, compounds are distributed in the scores plot according to their physicochemical properties.…”

Section: Results and Discussionmentioning

confidence: 99%

“…Nearly 500 substances with known toxicity values to at least one of the eight selected aquatic species have been considered in this work 7,[9][10][11][24][25][26][27][28][29][30][31][32][33] . A PCA analysis of the available solutes has been done according to their SPM molecular descriptors 14 .…”

Section: Selection Of the Solutes To Be Testedmentioning

confidence: 99%

Modeling Aquatic Toxicity through Chromatographic Systems

et al. 2017

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Environmental risk assessment requires information about the toxicity of the growing number of chemical products coming from different origins that can contaminate water and become toxicants to aquatic species or other living beings via the trophic chain. Direct toxicity measurements using sensitive aquatic species can be carried out but they may become expensive and ethically questionable. Literature refers to the use of chromatographic measurements that correlate to the toxic effect of a compound over a specific aquatic species as an alternative to get toxicity information. In this work, we have studied the similarity in the response of the toxicity to different species and we have selected eight representative aquatic species (including tadpoles, fish, water fleas, protozoan, and bacteria) with known nonspecific toxicity to chemical substances. Next, we have selected four chromatographic systems offering good perspectives for surrogation of the eight selected aquatic systems, and thus prediction of toxicity from the chromatographic measurement. Then toxicity has been correlated to the chromatographic retention factor. Satisfactory correlation results have been obtained to emulate toxicity in five of the selected aquatic species through some of the chromatographic systems. Other aquatic species with similar characteristics to these five representative ones could also be emulated by using the same chromatographic systems. The final aim of this study is to model chemical products toxicity to aquatic species by means of chromatographic systems to reduce in vivo testing.

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“…21) Substituted phenols included 2-, 3-and 4-nitrophenols; 4-chloro-2-nitrophenol; 2-and 4-chlorophenols; 2,4-dichlorophenol; 4-bromophenol; 2-bromo-4-methylphenol; 4-fluorophenol; 2-and 4-methoxyphenols; 2-and 4-methylphenols; 2,6-dimethylphenol; salicylaldehyde; 4-hydroxybenzaldehyde; salicylic acid; methyl 4-hydroxybenzoate; resorcinol, 3-aminophenol, 4-hydroxyacetophenone; 4-tertbutylphenol and phenol. See Eq.…”

Section: Rana Japonica Tadpolesmentioning

confidence: 99%

“…(10), the authors suggested that polar narcosis constituted the key mechanism for the acute toxicity of phenol derivatives to Rana japonica tadpoles. 21) A general and robust QSAR model (Eq. (11)) was also developed for the acute toxicity (24 hr semi-static exposure) of a series of 31 diverse phenols to Rana japonica tadpoles using four descriptors.…”

Section: Rana Japonica Tadpolesmentioning

confidence: 99%

QSAR of toxicology of substituted phenols

Selassie

Verma

2015

J. Pestic. Sci.

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The quantitative structure activity relationship paradigm provides an excellent avenue for investigating ligand-receptor interactions in medicinal chemistry/toxicology. Lateral validation of models formulated using this approach allows for a cohesive understanding of the mechanistic underpinnings of a specific class of related molecules. The diverse biological activities of substituted phenols (X-phenols) in organisms that run the gamut from protozoa to animals are herein examined and compared. Correlations between biological activities and physicochemical attributes of X-phenols reveal strong consistencies between various models. Two parameters in particular, hydrophobicity and electronic terms dominate the extent of interactions between these chemical entities and their molecular targets. Hydrophobicity is represented by π values or partition coefficients while electronic contributions are delineated by molecular orbital indices or Hammett sigma constants. They help us to define the similarity in these mechanistic models that allow for an understanding of forces that are at play at the molecular level.

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Quantitative Structure-Activity Relationships for the Toxicity to the Tadpole Rana japonica of Selected Phenols

Cited by 9 publications

References 14 publications

In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study

In vivo toxicity of nitroaromatics: A comprehensive quantitative structure–activity relationship study

Modeling Aquatic Toxicity through Chromatographic Systems

QSAR of toxicology of substituted phenols

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