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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
A DFT-based QSAR study of the toxicity of quaternary ammonium compounds on Chlorella vulgaris
Menjun Zhu1, Fei Ge, Runliang Zhu
1Department of Environmental Science and Engineering, Xiangtan University, Hunan, China.
Abstract:
The DFT-based descriptors were used to derive the quantitative structure-activity relationship (QSAR) models enabling the calculated quantum chemistry parameters to be correlated to the toxicity of quaternary ammonium compounds (QACs) on green alga Chlorella vulgaris. DFT/B3LYP level of theory with the 6-31G(d) basis set was applied to calculate a set of quantum chemistry descriptors for 11 QACs. The partial least squares (PLS) analysis implemented in Simca-P was employed to obtain the QSAR models. The optimal PLS model with the cumulative cross-validated regression coefficient (Q(cum)(2)=0.893) and the correlation coefficient between observed values and fitted values (R=0.975) explained 95.3% of the variance of the independent variables and 92.8% of the variance of the dependent variable. The results of this investigation show that alkyl chain lengths (CL), polarizability tense (alpha(zz)), the most positive net atomic charges on a hydrogen atom (q(H)(+)) and entropy (S(o)) are the major descriptors in governing the log(1/EC(50)) values of the QACs.

