Abstract
Predictive toxicology is a new emerging multifaceted research field aimed at protecting human health and environment from risks posed by chemicals. Such issue is of extreme public relevance and requires a multidisciplinary approach where the experience in medicinal chemistry is of utmost importance. Herein, we will survey some basic recommendations to gather good data and then will review three recent case studies to show how strategies of ligand- and structure-based molecular design, widely applied in medicinal chemistry, can be adapted to meet the more restrictive scientific and regulatory goals of predictive toxicology. In particular, we will report:
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Docking-based classification models to predict the estrogenic potentials of chemicals.
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Predicting the bioconcentration factor using biokinetics descriptors.
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Modeling oral sub-chronic toxicity using a customized k-nearest neighbors (k-NN) approach.
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Mangiatordi, G.F., Carotti, A., Novellino, E., Nicolotti, O. (2016). A Round Trip from Medicinal Chemistry to Predictive Toxicology. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 1425. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3609-0_19
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DOI: https://doi.org/10.1007/978-1-4939-3609-0_19
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