Integrative Approaches for Predicting In Vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-Term Biological Assays

ISSN: 1873-5294 (Online)
ISSN: 1568-0266 (Print)


Volume 14, 24 Issues, 2014


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Current Topics in Medicinal Chemistry

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  • 11th of 58 in Chemistry, Medicinal



Editor-in-Chief:
Allen B. Reitz
Fox Chase Chemical Diversity Center, Inc
Doylestown, PA
USA


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Integrative Approaches for Predicting In Vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-Term Biological Assays

Author(s): Yen Sia Low, Alexander Yeugenyevich Sedykh, Ivan Rusyn and Alexander Tropsha

Affiliation: 100K Beard Hall, Campus Box 7568, University of North Carolina, Chapel Hill, NC 27599-7568, USA.

Abstract

Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity.




Keywords: Bioinformatics, predictive toxicology, QSAR, systems pharmacology.

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Article Details

Volume: 14
Issue Number: 11
First Page: 1356
Last Page: 1364
Page Count: 9
DOI: 10.2174/1568026614666140506121116
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