QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data

Netzeva, Tatiana I.; Schultz, T. Wayne

doi:10.1016/j.chemosphere.2005.04.040

Cited by 58 publications

(45 citation statements)

References 22 publications

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“…Examples include models developed for algal toxicity of chlorophenols [17], anilines [18] and benzonitriles [19]; for daphnid toxicity of a-substituted phenylsulphonylacetates [20], quaternary alkylammonium sulphobetains [21], linear alkylbenzene sulphonates and ester sulphonates [22], benzoxazinone allelochemicals [23], for daphnid and fish toxicity of alcohol ethoxilate surfactants [24,25]; for ciliate toxicity of nitrobenzenes [26], alkanol and alkanamines [27], halogenated alkanes, alkanols and alkanitriles [28], lactones [29], phenols [30], and aromatic aldehydes [31], for algae, daphnid, fish, protozoa, bacteria and yeast toxicity of substituted mononitrobenzenes [32], amongst others. There are different motives (scientific, commercial and regulatory) for development of chemical class-based (Q)SARs.…”

Section: (Q)sar Models For Chemical Classesmentioning

confidence: 99%

Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

2008

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This paper reviews different approaches described in the literature for estimating the aquatic toxicity of chemical substances. It is based on an extended review performed by the European Chemicals Bureau of the European Commissions Joint Research Centre in support of the development of technical guidance for the implementation of the REACH legislation, and is one of a series of minireviews in this journal. The paper is organised by approach for (Q)SAR development and includes a review of: (i) (Q)SARs for acute aquatic toxicity by chemical class, (ii) (Q)SARs for acute aquatic toxicity by mode of action, (iii) review of statistically derived (Q)SARs, (iv) structural alerts for excess aquatic toxicity and (v) expert systems that combine structural rules and multiple (Q)SAR models to predict aquatic toxicological endpoints. Directions and recommendations for further research are also provided.

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Section: (Q)sar Models For Chemical Classesmentioning

confidence: 99%

Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

2008

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“…Data set for analysis QSTR analysis was performed using the pIC 50 of 77 selected aromatic aldehydes to Tetrahymena pyriformis as reported in [4], the values of the 14 chemical descriptors are shown in table 2. The obtained matrix provides information on the positive or negative correlation between descriptors.…”

Section: Resultsmentioning

confidence: 99%

“…To determine a quantitative structure-toxicity relationship, we studied a series of 77 selected aromatic aldehydes for their acute toxicity against the protozoan ciliate Tetrahymena pyriformis [4]. 66 molecules were selected to propose the quantitative model (training set) as well as 11 compounds that were not used in the training set were selected randomly served to test the performance of the proposed model (test set).…”

Section: Experimental Datamentioning

confidence: 99%

Quantitative structure - toxicity relationship studies of aromatic aldehydes to Tetrahymena pyriformis base d on electronic and topological descriptors

Oussa¹,

Elidrissi²,

Ghamali³

et al. 2018

jmes

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“…Nt ¼ log N log max (3) where N is the number of vertices in a molecular skeletal graph, and max is the maximum eigenvalue of matrix D l . For example, the nonhydrogen skeletal description and the revised distance matrix for 4,4-dimethyl-2-pentanone are given as below (see Figure 2): …”

Section: Calculation Of Topological Descriptor Ntmentioning

confidence: 99%

A novel semi‐empirical topological descriptor Nt and the application to study on QSPR/QSAR

Zhou¹,

Nie²,

Li³

2007

J Comput Chem

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A novel semi-empirical topological descriptor Nt was proposed by revising the traditional distance matrix based on the equilibrium electronegativity and the relative bond length. Nt can not only efficiently distinguish structures of organic compounds containing multiple bonds and/or heteroatoms, but also possess good applications of QSPR/QSAR (quantitative structure-property/activity relationships) to a large diverse set of compounds, which are alkanes, alkenes, alkynes, aldehydes, ketones, thiols, and alkoxy silicon chlorides with all the correlation coefficients of the models over 0.99. The LOO CV (leave-one-out cross-validation) method was used to testify the stability and predictive ability of the models. The validation results verify the good stability and predictive ability of the models employing the cross-validation parameters: RCV, SEPCV and SCV, which demonstrate the wide potential of the Nt descriptor for applications to QSPR/QSAR.

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QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data

Cited by 58 publications

References 22 publications

Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

Review of (Quantitative) Structure–Activity Relationships for Acute Aquatic Toxicity

Quantitative structure - toxicity relationship studies of aromatic aldehydes to Tetrahymena pyriformis base d on electronic and topological descriptors

A novel semi‐empirical topological descriptor Nt and the application to study on QSPR/QSAR

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