QSAR models for predicting in vivo aquatic toxicity of chlorinated alkanes to fish.
Quantitative structure-activity relationship (QSAR) models are expected to play a crucial role in reducing the number of animals to be used for toxicity testing resulting from the adoption of the new European Union chemical control system called Registration, Evaluation, and Authorization of Chemicals (REACH). The objective of the present study was to generate in vitro acute toxicity data that could be used to develop a QSAR model to describe acute in vivo toxicity of chlorinated alkanes. Cytotoxicity of a series of chlorinated alkanes to Chinese hamster ovary (CHO) cells was observed at concentrations similar to those that have been shown previously to be toxic to fish. Strong correlations exist between the acute in vitro toxicity of the chlorinated alkanes and (i) hydrophobicity [modeled by the calculated log K ow (octanol-water partition coefficient); r (2) = 0.883 and r int (2) = 0.854] and (ii) in vivo acute toxicity to fish ( r (2) = 0.758). A QSAR model has been developed to predict in vivo acute toxicity to fish, based on the in vitro data and even on in silico log K ow data only. The developed QSAR model is applicable to chlorinated alkanes with up to 10 carbon atoms, up to eight chlorine atoms, and log K ow values lying within the range from 1.71 to 5.70. Out of the 100204 compounds on the European Inventory of Existing Chemicals (EINECS), our QSAR model covers 77 (0.1%) of them. Our findings demonstrate that in vitro experiments and even in silico calculations can replace animal experiments in the prediction of the acute toxicity of chlorinated alkanes.
Zvinavashe
Elton
E
Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen, Division of Biochemistry, Wageningen University, Dreijenlaan 3, 6703 HA Wageningen, The Netherlands. elton.zvinavashe@wur.nl
van den Berg
Hans
H
Soffers
Ans E M F
AE
Vervoort
Jacques
J
Freidig
Andreas
A
Murk
Albertinka J
AJ
Rietjens
Ivonne M C M
IM
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D016466:CHO Cells; D002470:Cell Survival / Q000187:drug effects; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D006224:Cricetinae; D003412:Cricetulus; D005399:Fishes / Q000502:physiology*; D006843:Hydrocarbons, Chlorinated / Q000737:chemistry* / Q000633:toxicity*; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D013778:Tetrazolium Salts; D013844:Thiazoles
D006843:Hydrocarbons, Chlorinated; D013778:Tetrazolium Salts; D013844:Thiazoles; C022616:thiazolyl blue