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Open AccessJournal ArticleDOI

QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action.

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TLDR
The Hierarchical Technology for Quantitative Structure–Activity Relationships (HiT QSAR) was applied to 95 diverse nitroaromatic compounds tested for their toxicity and it was shown that mutual influence of substituents in benzene ring plays the determining role in toxicity variation.
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).

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Journal ArticleDOI

Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research

TL;DR: The need for a standardized chemical data curation strategy that should be followed at the onset of any molecular modeling investigation is emphasized and it is demonstrated that in some cases rigorously developed QSAR models could be even used to correct erroneous biological data associated with chemical compounds.
Book ChapterDOI

Tetrahymena in the laboratory: strain resources, methods for culture, maintenance, and storage.

TL;DR: This chapter presents a brief description of many available Tetrahymena strains and lists possible resources for obtaining viable cultures of T. thermophila and other TetrahYmena species.
Journal ArticleDOI

From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles

TL;DR: The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles and suggest different mechanisms of nanotoxicity for these two types of cells.
Journal ArticleDOI

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.

TL;DR: This study aims to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitized individuals, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals.
References
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Journal ArticleDOI

Classification and regression trees

TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Book

Classification and regression trees

Leo Breiman
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Journal ArticleDOI

Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

TL;DR: The main features of the CoMFA approach, exemplified by analyses of the affinities of 21 varied steroids to corticosteroid and testosterone-binding globulins, and a number of advances in the methodology of molecular graphics are described.
Journal ArticleDOI

Beware of q2

TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.
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