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Research Articles

Quantitative structure–toxicity relationship models for predication of toxicity of ionic liquids toward leukemia rat cell line IPC-81 based on index of ideality of correlation

, ORCID Icon & ORCID Icon
Pages 302-312 | Received 08 Sep 2021, Accepted 26 Oct 2021, Published online: 12 Dec 2021
 

Abstract

The application of ionic liquids (ILs) as green solvents has attracted the attention of the scientific community. However, ILs may play the role of toxins. Even though ionic liquids may assist to minimize air pollution, but their discharge into aquatic ecosystems might result in significant water pollution due to their potential toxicity and inaccessibility to biodegradation. Recently, more attention has been paid to the toxicity of ILs on plants, bacteria, and humans. Here, a quantitative structure–toxicity relationship study (QSTR) based on the Monte Carlo method of CORAL software has been applied to estimate the logarithm of the half-maximal effective concentration of toxicity of ILs against leukemia rat cell line IPC-81 (logEC50). A hybrid optimal descriptor is used to build QSTR models for a large set of 304 diverse ILs including ammonium, imidazolium, morpholinium, phosphonium, piperidinium, pyridinium, pyrrolidinium, quinolinium, sulfonium, and protic ILs. The SMILES notations of ILs are utilized to compute the descriptor correlation weight (DCW). Four splits are made from the whole dataset and each split is randomly divided into four sets (training subsets and validation set). The index of ideality of correlation (IIC) is applied to evaluate the authenticity and robustness of the QSTR models. A QSTR model with statistical parameters R2 = 0.85, CCC = 0.92, Q2 = 0.84, and MAE = 0.25 for the validation set of the best split is considered as a prime model. The outliers and promoters of increase/decrease of logEC50 are extracted and the mechanistic interpretation of effective descriptors for the model is also offered.

    Highlights

  • Global SMILES-based QSAR model was developed to predict the toxicity of ILs.

  • The CORAL software is used to model the ILs toxicity on IPC-81 leukemia rat cell line.

  • IIC is tested as a criterion of predictive potential.

  • The toxicological effects of ILs are discussed based on the proposed model.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Acknowledgments

The authors are thankful to Dr Andrey A. Toropov and Dr Alla P. Toropova for providing CORAL software. The authors are also thankful to the authorities of respective universities for providing infrastructure.

Disclosure statement

The authors declare no conflicts of interest.

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