» Articles » PMID: 21714735

QSAR Analysis of the Toxicity of Nitroaromatics in Tetrahymena Pyriformis: Structural Factors and Possible Modes of Action

Overview
Date 2011 Jul 1
PMID 21714735
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

The Hierarchical Technology for Quantitative Structure-Activity Relationships (HiT QSAR) was applied to 95 diverse nitroaromatic compounds (including some widely known explosives) tested for their toxicity (50% inhibition growth concentration, IGC₅₀) against the ciliate Tetrahymena pyriformis. The dataset was divided into subsets according to putative mechanisms of toxicity. The Classification and Regression Trees (CART) approach implemented within HiT QSAR has been used for prediction of mechanism of toxicity for new compounds. The resulting models were shown to have ~80% accuracy for external datasets indicating that the mechanistic dataset division was sensible. The Partial Least Squares (PLS) statistical approach was then used to develop 2D QSAR models. Validated PLS models were explored to: (1) elucidate the effects of different substituents in nitroaromatic compounds on toxicity; (2) differentiate compounds by probable mechanisms of toxicity based on their structural descriptors; and (3) analyse the role of various physical-chemical factors responsible for compounds' toxicity. Models were interpreted in terms of molecular fragments promoting or interfering with toxicity. It was also shown that mutual influence of substituents in benzene ring plays the determining role in toxicity variation. Although chemical mechanism based models were statistically significant and externally predictive (r²(ext) = 0.64 for the external set of 63 nitroaromatics identified after all calculations have been completed), they were also shown to have limited coverage (57% for modelling and 76% for external set).

Citing Articles

Modeling interactions between Heparan sulfate and proteins based on the Heparan sulfate microarray analysis.

Melo-Filho C, Su G, Liu K, Muratov E, Tropsha A, Liu J Glycobiology. 2024; 34(7).

PMID: 38836441 PMC: 11180703. DOI: 10.1093/glycob/cwae039.


Quantitative Structure-Activity Relationship (QSAR) Studies on the Toxic Effects of Nitroaromatic Compounds (NACs): A Systematic Review.

Huang T, Sun G, Zhao L, Zhang N, Zhong R, Peng Y Int J Mol Sci. 2021; 22(16).

PMID: 34445263 PMC: 8395302. DOI: 10.3390/ijms22168557.


Simplex representation of molecular structure as universal QSAR/QSPR tool.

Kuzmin V, Artemenko A, Ognichenko L, Hromov A, Kosinskaya A, Stelmakh S Struct Chem. 2021; 32(4):1365-1392.

PMID: 34177203 PMC: 8218296. DOI: 10.1007/s11224-021-01793-z.


Computational Models Identify Several FDA Approved or Experimental Drugs as Putative Agents Against SARS-CoV-2.

Bobrowski T, Alves V, Melo-Filho C, Korn D, Auerbach S, Schmitt C ChemRxiv. 2020; .

PMID: 32511287 PMC: 7252448. DOI: 10.26434/chemrxiv.12153594.


Optoelectronic Properties of C and C Fullerene Derivatives: Designing and Evaluating Novel Candidates for Efficient P3HT Polymer Solar Cells.

Roy J, Kar S, Leszczynski J Materials (Basel). 2019; 12(14).

PMID: 31315218 PMC: 6678454. DOI: 10.3390/ma12142282.


References
1.
Fourches D, Muratov E, Tropsha A . Trust, but verify: on the importance of chemical structure curation in cheminformatics and QSAR modeling research. J Chem Inf Model. 2010; 50(7):1189-204. PMC: 2989419. DOI: 10.1021/ci100176x. View

2.
Hasegawa K, Miyashita Y, Funatsu K . GA strategy for variable selection in QSAR studies: GA-based PLS analysis of calcium channel antagonists. J Chem Inf Comput Sci. 1997; 37(2):306-10. DOI: 10.1021/ci960047x. View

3.
Kuzmin V, Artemenko A, Muratov E, Volineckaya I, Makarov V, Riabova O . Quantitative structure-activity relationship studies of [(biphenyloxy)propyl]isoxazole derivatives. Inhibitors of human rhinovirus 2 replication. J Med Chem. 2007; 50(17):4205-13. DOI: 10.1021/jm0704806. View

4.
Cronin M, Gregory B, Schultz T . Quantitative structure-activity analyses of nitrobenzene toxicity to Tetrahymena pyriformis. Chem Res Toxicol. 1998; 11(8):902-8. DOI: 10.1021/tx970166m. View

5.
Muratov E, Varlamova E, Artemenko A, Khristova T, Kuzmin V, Makarov V . QSAR analysis of [(biphenyloxy)propyl]isoxazoles: agents against coxsackievirus B3. Future Med Chem. 2011; 3(1):15-27. DOI: 10.4155/fmc.10.278. View