E-State Modeling of Fish Toxicity Independent of 3D Structure Information

Topological structure methods are used to model fish toxicity against three classes of organic chemicals. The models were obtained independent of 3D structure information. Further, no mechanism of partitioning was assumed, thus avoiding the problems associated with selection of partitioning system f...

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Bibliographic Details
Published inSAR and QSAR in environmental research Vol. 14; no. 2; pp. 113 - 129
Main Authors Rose, K., Hall, L.H.
Format Journal Article
LanguageEnglish
Published England Taylor & Francis Group 01.04.2003
Subjects
Aniline Compounds - chemistry
Aniline Compounds - toxicity
Animals
Chemical Phenomena
Chemistry, Physical
Electrotopological State
Fish Toxicity
Fishes
Hydrocarbons, Aromatic - chemistry
Hydrocarbons, Aromatic - toxicity
Industrial Waste
Log P
Mathematics
Models, Chemical
Molecular Connectivity
Phenols - chemistry
Phenols - toxicity
Qsar
Quantitative Structure-Activity Relationship
Topological Method
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Summary:Topological structure methods are used to model fish toxicity against three classes of organic chemicals. The models were obtained independent of 3D structure information. Further, no mechanism of partitioning was assumed, thus avoiding the problems associated with selection of partitioning system for computation of log P . QSAR models were developed for a set of 92 compounds, including phenols, anilines and substituted aromatic hydrocarbons, yielding excellent statistics: r 2 =0.87, s =0.25 and q 2 =0.85 leave-one-out (LOO), that are better than those reported in the literature. The model is based on molecular connectivity valence chi-1 index [ 1 h v ], the atom type E-State indices for chlorine [ S T (-Cl)] and for ether oxygen [ S T (-O-)], and the maximum hydrogen E-State atom value in a molecule [H max ]. Each of the subgroups was also separately well modeled. The model for the full set is validated through use of external validation test sets and ten-fold cross-validation (repeated three times). The quality of the validation statistics supports the claim that the model may be used for estimation of pLC 50 values for similar molecules. Detailed structure interpretation is given for the descriptors in the model. These four structure descriptors encode influence of molecular context of groups as well as counts of those groups, in addition to molecular skeletal structure.
ISSN:1062-936X
1029-046X
DOI:10.1080/1062936031000073144