QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide.

Abstract:

:Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC50) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures.

journal_name

Chemosphere

journal_title

Chemosphere

authors

Qin LT,Chen YH,Zhang X,Mo LY,Zeng HH,Liang YP

doi

10.1016/j.chemosphere.2018.01.142

subject

Has Abstract

pub_date

2018-05-01 00:00:00

pages

122-129

eissn

0045-6535

issn

1879-1298

pii

S0045-6535(18)30159-0

journal_volume

198

pub_type

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