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The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study

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Abstract

The present study applies the Hierarchical Technology for Quantitative Structure–Activity Relationships (HiT QSAR) for (i) evaluation of the influence of the characteristics of 28 nitroaromatic compounds (some of which belong to a widely known class of explosives) as to their toxicity; (ii) prediction of toxicity for new nitroaromatic derivatives; (iii) analysis of the effects of substituents in nitroaromatic compounds on their toxicity in vivo. The 50% lethal dose concentration for rats (LD50) was used to develop the QSAR models based on simplex representation of molecular structure. The preliminary 1D QSAR results show that even the information on the composition of molecules reveals the main tendencies of changes in toxicity. The statistic characteristics for partial least squares 2D QSAR models are quite satisfactory (R 2 = 0.96–0.98; Q 2 = 0.91–0.93; R 2 test = 0.89–0.92), which allows us to carry out the prediction of activity for 41 novel compounds designed by the application of new combinations of substituents represented in the training set. The comprehensive analysis of toxicity changes as a function of substituent position and nature was carried out. Molecular fragments that promote and interfere with toxicity were defined on the basis of the obtained models. It was shown that the mutual influence of substituents in the benzene ring plays a crucial role regarding toxicity. The influence of different substituents on toxicity can be mediated via different C–H fragments of the aromatic ring.

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Notes

  1. Number of groups is a tuning parameter of the model and can be varied.

Abbreviations

AVS:

Automatic variables selection

DA:

Applicability domain

GA:

Genetic algorithm

HiT QSAR:

Hierarchical QSAR technology

HQSAR:

Hologram QSAR approach

LD50 :

50% lethal dose concentration

PLS:

Partial least squares or projection on latent structures statistical method

Q 2 :

Cross-validation determination coefficient

QSAR/QSPR:

Quantitative structure–activity/property relationship

R 2 :

Determination coefficient for training set

R 2 test :

Determination coefficient for test set

SD:

Simplex descriptor

SiRMS:

Simplex representation of molecular structure QSAR approach

TV:

Trend-vector statistical method

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Acknowledgments

We appreciate and thank Dr. John Cullinane, ERDC Technical Director for Military Environmental Engineering and Science and Dr. Richard E. Price, Environmental Division Chief, ERDC, for their support and encouragement. Permission was granted by the Chief of Engineers to publish this information. This content does not necessarily reflect the position or the policy of the government, and no official endorsement should be inferred. The authors are also thankful to Drs. B. Rasulev, A. Toropov and O. Isaev for fruitful discussion and useful comments.

Funding

US Army Environmental Quality Technology Program (grant W912Z-04-P-139) administrated by the US Army Engineer Research and Development Center; US Army Engineer Research and Development Center CMCM program (grant 2T346GM007672-25A1). The authors confirm independence from the sponsors; the content of the article has not been influenced by the sponsors.

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Authors and Affiliations

  1. Department of Chemistry, Computational Center for Molecular Structure and Interactions, Jackson State University, 1400 J.R. Lynch St, Jackson, MS, 39217, USA

    Victor E. Kuz’min, Eugene N. Muratov, Leonid Gorb & Jerzy Leszczynski

  2. A.V. Bogatsky Physical-Chemical Institute, National Academy of Sciences of Ukraine, Odessa, Ukraine

    Victor E. Kuz’min, Eugene N. Muratov & Anatoly G. Artemenko

  3. US Army ERDC (SpecPro), Vicksburg, MS, 39180, USA

    Leonid Gorb

  4. US Army ERDC, Vicksburg, MS, 39180, USA

    Mohammad Qasim

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  1. Victor E. Kuz’min
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  2. Eugene N. Muratov
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Correspondence to Jerzy Leszczynski.

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Kuz’min, V.E., Muratov, E.N., Artemenko, A.G. et al. The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study. J Comput Aided Mol Des 22, 747–759 (2008). https://doi.org/10.1007/s10822-008-9211-x

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